---

Publications

2024

• Scarabaggio, P., Carli, R., Grammatico, S. & Dotoli, M. (2024) Local Generalized Nash Equilibria with Nonconvex Coupling Constraints. IN IEEE Transactions on Automatic Control, .. doi:10.1109/TAC.2024.3462553
  [BibTeX] [Abstract] [Download PDF]

  We address a class of Nash games with nonconvex coupling constraints for which we define a novel notion of local equilibrium, here named local generalized Nash equilibrium (LGNE). Our first technical contribution is to show the stability in the game theoretic sense of these equilibria on a specific local subset of the original feasible set. Remarkably, we show that the proposed notion of local equilibrium can be equivalently formulated as the solution of a quasi-variational inequality with equal Lagrange multipliers. Next, under the additional proximal smoothness assumption of the coupled feasible set, we define conditions for the existence and local uniqueness of a LGNE. To compute such an equilibrium, we propose two discrete-time dynamics, or fixed-point iterations implemented in a centralized fashion. Our third technical contribution is to prove convergence under (strongly) monotone assumptions on the pseudo- gradient mapping of the game and proximal smoothness of the coupled feasible set. Finally, we apply our theoretical results to a noncooperative version of the optimal power flow control problem. © 1963-2012 IEEE.

  @ARTICLE{Scarabaggio2024,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Grammatico, Sergio and Dotoli, Mariagrazia},
  title = {Local Generalized Nash Equilibria with Nonconvex Coupling Constraints},
  year = {2024},
  journal = {IEEE Transactions on Automatic Control},
  doi = {10.1109/TAC.2024.3462553},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204423506&doi=10.1109%2fTAC.2024.3462553&partnerID=40&md5=a06e7fdba1764046b6ce415201f6be5e},
  abstract = {We address a class of Nash games with nonconvex coupling constraints for which we define a novel notion of local equilibrium, here named local generalized Nash equilibrium (LGNE). Our first technical contribution is to show the stability in the game theoretic sense of these equilibria on a specific local subset of the original feasible set. Remarkably, we show that the proposed notion of local equilibrium can be equivalently formulated as the solution of a quasi-variational inequality with equal Lagrange multipliers. Next, under the additional proximal smoothness assumption of the coupled feasible set, we define conditions for the existence and local uniqueness of a LGNE. To compute such an equilibrium, we propose two discrete-time dynamics, or fixed-point iterations implemented in a centralized fashion. Our third technical contribution is to prove convergence under (strongly) monotone assumptions on the pseudo- gradient mapping of the game and proximal smoothness of the coupled feasible set. Finally, we apply our theoretical results to a noncooperative version of the optimal power flow control problem. © 1963-2012 IEEE.},
  author_keywords = {Generalized nash equilibrium; multi-agent systems; non convex generalized games; variational inequalities},
  keywords = {Game theory; Coupling constraints; Feasible set; Generalized Nash equilibrium; Local equilibrium; Multiagent systems (MASs); Nash games; Non convex generalized game; Nonconvex; Technical contribution; Variational inequalities; Lagrange multipliers},
  type = {Article},
  publication_stage = {Article in press},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Hybrid Gold Open Access}
  }

• Dammacco, L., Carli, R., Lazazzera, V., Fiorentino, M. & Dotoli, M. (2024) Virtual Design of Complex Manufacturing Systems by Digital Technologies: The Case of an Italian Automotive Company. IN Lecture Notes in Mechanical Engineering, .383 – 390. doi:10.1007/978-3-031-58094-9_42
  [BibTeX] [Abstract] [Download PDF]

  In recent years, many industrial companies have embraced new technologies for Industry 4.0, the fourth industrial revolution. This global manufacturing trend connects real-life industry with the virtual world. Digitalization tools play a crucial role in allowing companies to decrease design and production costs, as well as accelerate the product development process. Regarding an actual industrial case study of an Italian automotive company, this work focuses on the use of digital technologies in designing complex manufacturing systems, showing the benefits that can be obtained with respect to traditional methods. Digitalization tools have aided in the design of intricate manufacturing systems that demand advanced automation to optimize the arrangement, workflow, and equipment configuration within a manufacturing facility or production line. After examining the features of the virtual approach employed by the considered company, the virtual commissioning of a screwing station for an electric axle assembly line is analyzed in detail to show the efficiency and effectiveness of digitalization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

  @ARTICLE{Dammacco2024383,
  author = {Dammacco, Lucilla and Carli, Raffaele and Lazazzera, Vito and Fiorentino, Michele and Dotoli, Mariagrazia},
  title = {Virtual Design of Complex Manufacturing Systems by Digital Technologies: The Case of an Italian Automotive Company},
  year = {2024},
  journal = {Lecture Notes in Mechanical Engineering},
  pages = {383 – 390},
  doi = {10.1007/978-3-031-58094-9_42},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193606990&doi=10.1007%2f978-3-031-58094-9_42&partnerID=40&md5=f032f88abf2548dcd8fabb0be4cd138a},
  abstract = {In recent years, many industrial companies have embraced new technologies for Industry 4.0, the fourth industrial revolution. This global manufacturing trend connects real-life industry with the virtual world. Digitalization tools play a crucial role in allowing companies to decrease design and production costs, as well as accelerate the product development process. Regarding an actual industrial case study of an Italian automotive company, this work focuses on the use of digital technologies in designing complex manufacturing systems, showing the benefits that can be obtained with respect to traditional methods. Digitalization tools have aided in the design of intricate manufacturing systems that demand advanced automation to optimize the arrangement, workflow, and equipment configuration within a manufacturing facility or production line. After examining the features of the virtual approach employed by the considered company, the virtual commissioning of a screwing station for an electric axle assembly line is analyzed in detail to show the efficiency and effectiveness of digitalization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},
  author_keywords = {Automotive; Complex Manufacturing Systems; Digital Technologies; Industry 4.0; Virtual Commissioning},
  keywords = {Costs; Electric lines; Product design; Virtual reality; Automotive companies; Automotives; Complex manufacturing systems; Digital technologies; Global manufacturing; Industrial companies; Industrial revolutions; Virtual commissioning; Virtual design; Virtual worlds; Industry 4.0},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Mignoni, N., Carli, R. & Dotoli, M. (2024) Optimal Decision Strategies for the Generalized Cuckoo Card Game. IN IEEE Transactions on Games, 16.185 – 194. doi:10.1109/TG.2023.3239795
  [BibTeX] [Abstract] [Download PDF]

  Cuckoo is a popular card game, which originated in France during the 15th century, and then, spread throughout Europe, where it is currently well-known under distinct names and with different variants. Cuckoo is an imperfect information game-of-chance, which makes the research regarding its optimal strategies determination interesting. The rules are simple: each player receives a covered card from the dealer; starting from the player at the dealer’s left, each player looks at its own card and decides whether to exchange it with the player to their left, or keep it; the dealer plays at last and, if it decides to exchange card, it draws a random one from the remaining deck; the player(s) with the lowest valued card lose(s) the round. We formulate the gameplay mathematically and provide an analysis of the optimal decision policies. Different card decks can be used for this game, e.g., the standard 52-card deck or the Italian 40-card deck. We generalize the decision model for an arbitrary number of decks’ cards, suites, and players. Finally, through numerical simulations, we compare the determined optimal decision strategy against different benchmarks, showing that the strategy outperforms the random and naive policies and approaches the performance of the ideal oracle. © 2018 IEEE.

  @ARTICLE{Mignoni2024185,
  author = {Mignoni, Nicola and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Optimal Decision Strategies for the Generalized Cuckoo Card Game},
  year = {2024},
  journal = {IEEE Transactions on Games},
  volume = {16},
  number = {1},
  pages = {185 – 194},
  doi = {10.1109/TG.2023.3239795},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147283813&doi=10.1109%2fTG.2023.3239795&partnerID=40&md5=3913f77d7fa5cb1c10485170111b23d2},
  abstract = {Cuckoo is a popular card game, which originated in France during the 15th century, and then, spread throughout Europe, where it is currently well-known under distinct names and with different variants. Cuckoo is an imperfect information game-of-chance, which makes the research regarding its optimal strategies determination interesting. The rules are simple: each player receives a covered card from the dealer; starting from the player at the dealer's left, each player looks at its own card and decides whether to exchange it with the player to their left, or keep it; the dealer plays at last and, if it decides to exchange card, it draws a random one from the remaining deck; the player(s) with the lowest valued card lose(s) the round. We formulate the gameplay mathematically and provide an analysis of the optimal decision policies. Different card decks can be used for this game, e.g., the standard 52-card deck or the Italian 40-card deck. We generalize the decision model for an arbitrary number of decks' cards, suites, and players. Finally, through numerical simulations, we compare the determined optimal decision strategy against different benchmarks, showing that the strategy outperforms the random and naive policies and approaches the performance of the ideal oracle. © 2018 IEEE.},
  author_keywords = {Card games; games of chance; optimal decision strategy; optimization},
  keywords = {Artificial intelligence; Benchmarking; Emotion Recognition; 15th century; Card games; Computational modelling; Cultural difference; Emotion recognition; Europe; Game; Games of chance; Optimal decision strategy; Optimisations; Numerical models},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1; All Open Access, Hybrid Gold Open Access}
  }

• Vlacic, L., Huang, H., Dotoli, M., Wang, Y., Ioannou, P. A., Fan, L., Wang, X., Carli, R., Lv, C., Li, L., Na, X., Han, Q. & Wang, F. (2024) Automation 5.0: The Key to Systems Intelligence and Industry 5.0. IN IEEE/CAA Journal of Automatica Sinica, 11.1723 – 1727. doi:10.1109/JAS.2024.124635
  [BibTeX] [Abstract] [Download PDF]

  Automation has come a long way since the early days of mechanization, i.e., the process of working exclusively by hand or using animals to work with machinery. The rise of steam engines and water wheels represented the first generation of industry, which is now called Industry 1.0. Subsequently, Industry 2.0 witnessed the development of electric power and assembly lines. Later on, programmable logic controllers and Human Machine Interfaces (HMI) were the new productivity tools in Industry 3.0, which enabled precise and consistent production. In recent years, Industry 4.0 absorbed the latest technologies of Internet of Things (IoT), Artificial Intelligence (AI), and big data, making production processes integrated, interconnected, and smart. Nowadays, Industry 5.0 has been proposed, which emphasizes human-centric automation. Specifically, the new concept of automation in Industry 5.0, named Automation 5.0, is no longer about how to create machinery to replace humans. Instead, it aims to reach organic interactions and cooperation between humans and machines, meeting the goal of ‘6S’-Safety, Security, Sustainability, Sensitivity, Service, and Smartness [1]-[4]-and the overall objective of deploying automation for the better, human-friendly, and smarter industry. © 2014 Chinese Association of Automation.

  @ARTICLE{Vlacic20241723,
  author = {Vlacic, Ljubo and Huang, Hailong and Dotoli, Mariagrazia and Wang, Yutong and Ioannou, Petros A. and Fan, Lili and Wang, Xingxia and Carli, Raffaele and Lv, Chen and Li, Lingxi and Na, Xiaoxiang and Han, Qing-Long and Wang, Fei-Yue},
  title = {Automation 5.0: The Key to Systems Intelligence and Industry 5.0},
  year = {2024},
  journal = {IEEE/CAA Journal of Automatica Sinica},
  volume = {11},
  number = {8},
  pages = {1723 – 1727},
  doi = {10.1109/JAS.2024.124635},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199527866&doi=10.1109%2fJAS.2024.124635&partnerID=40&md5=bdd9d87d98cc8da08156c45367eb9eb2},
  abstract = {Automation has come a long way since the early days of mechanization, i.e., the process of working exclusively by hand or using animals to work with machinery. The rise of steam engines and water wheels represented the first generation of industry, which is now called Industry 1.0. Subsequently, Industry 2.0 witnessed the development of electric power and assembly lines. Later on, programmable logic controllers and Human Machine Interfaces (HMI) were the new productivity tools in Industry 3.0, which enabled precise and consistent production. In recent years, Industry 4.0 absorbed the latest technologies of Internet of Things (IoT), Artificial Intelligence (AI), and big data, making production processes integrated, interconnected, and smart. Nowadays, Industry 5.0 has been proposed, which emphasizes human-centric automation. Specifically, the new concept of automation in Industry 5.0, named Automation 5.0, is no longer about how to create machinery to replace humans. Instead, it aims to reach organic interactions and cooperation between humans and machines, meeting the goal of '6S'-Safety, Security, Sustainability, Sensitivity, Service, and Smartness [1]-[4]-and the overall objective of deploying automation for the better, human-friendly, and smarter industry. © 2014 Chinese Association of Automation.},
  keywords = {Accident prevention; Electric lines; Industry 4.0; Internet of things; Programmable logic controllers; Assembly line; Electric power lines; Human Machine Interface; Human-centric; Latest technology; Mechanisation; Production process; Productivity tools; System intelligence; Water wheel; Automation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Tresca, G., Salem, H., Cavone, G., Zgaya-Biau, H., Ben-Othman, S., Hammadi, S. & Dotoli, M. (2024) A Matheuristic Approach for Delivery Planning and Dynamic Vehicle Routing in Logistics 4.0. IN IEEE Transactions on Automation Science and Engineering, .1–21. doi:10.1109/TASE.2024.3393507
  [BibTeX] [Abstract] [Download PDF]

  In distribution logistics, the planning of vehicles’ routes and vehicles’ loads are traditionally managed separately, despite these activities are correlated. This often leads to various re-designs to make the routes and load plans compatible and applicable in practice. Moreover, the planned routes, which are static by definition, cannot always cope with unexpected events. Traffic congestion, vehicle failures, adverse meteorological conditions, and further undesired events can make the planned routes inapplicable and require vehicles’ re-routing. This results in lower service levels, undesired delays, and higher costs for logistics companies. With the aim of overcoming the above limitations, this work proposes a novel approach based on a matheuristic algorithm that jointly solves the problem of delivery planning and dynamic vehicle routing to automate the delivery process in a logistics 4.0 perspective. The presented algorithm includes two different phases: the static phase, which is executed offline and in advance with respect to the delivery day, and the dynamic phase, which is executed in real-time to cope with unexpected events during the delivery. For the first phase, a matheuristic approach is defined to efficiently solve the combined vehicle routing and loading problems. Differently, for the second phase, a genetic algorithm is proposed to re-route vehicles in real-time, considering both the redefinition in real-time of the nominal trip and/or of the sequence of the customers to be visited. The algorithm is tested both on a literature benchmark and on a real dataset provided by an Italian logistics company. The obtained results show that, on the one hand, the proposed algorithm can automatically provide feasible solutions that minimise travel costs, total travelled distance, and empty space on the vehicles; on the other hand, it can ensure in real-time effective re-routing solutions in case of unexpected events occurring during delivery. Note to Practitioners—This work is motivated by the need for facilitating the operations of planning and routing deliveries in the external logistics sector. We propose an algorithm that automatically generates feasible routing and loading plans for a set of Transport Units (TUs) (i.e., the static phase), and then updates in real-time the nominal route in case of unexpected events (i.e., the dynamic phase). More specifically, the first phase of the algorithm takes as input the set of different clients, the list of products packed into bins (i.e., standard packing units) to be delivered to each client, and the set of transport units available for the deliveries, and provides as output the number and type of TUs to be used, the composition of the bins in each transport unit, and the corresponding route, while optimising the space occupation in each TU and the travel costs. The second phase, instead, takes as input the nominal routes computed in the first phase and, in case of unexpected events (e.g., accidents, slowdowns, etc.) affecting one or more routes, it re-routes the involved trucks guaranteeing the maximum efficiency in regards to travel cost, travel time, and quality of service. The adoption of this algorithm by logistic companies supports the automation of the delivery process and drastically improves the efficiency of logistic operations, with particular regard to the number of used TUs, costs, safety of goods, and customers’ satisfaction. IEEE

  @ARTICLE{Tresca20241,
  author = {Tresca, Giulia and Salem, Hadrien and Cavone, Graziana and Zgaya-Biau, Hayfa and Ben-Othman, Sarah and Hammadi, Slim and Dotoli, Mariagrazia},
  title = {A Matheuristic Approach for Delivery Planning and Dynamic Vehicle Routing in Logistics 4.0},
  year = {2024},
  journal = {IEEE Transactions on Automation Science and Engineering},
  pages = {1–21},
  doi = {10.1109/TASE.2024.3393507},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192183436&doi=10.1109%2fTASE.2024.3393507&partnerID=40&md5=0050575ea49331e008393fe1ec273d7d},
  abstract = {In distribution logistics, the planning of vehicles’ routes and vehicles’ loads are traditionally managed separately, despite these activities are correlated. This often leads to various re-designs to make the routes and load plans compatible and applicable in practice. Moreover, the planned routes, which are static by definition, cannot always cope with unexpected events. Traffic congestion, vehicle failures, adverse meteorological conditions, and further undesired events can make the planned routes inapplicable and require vehicles’ re-routing. This results in lower service levels, undesired delays, and higher costs for logistics companies. With the aim of overcoming the above limitations, this work proposes a novel approach based on a matheuristic algorithm that jointly solves the problem of delivery planning and dynamic vehicle routing to automate the delivery process in a logistics 4.0 perspective. The presented algorithm includes two different phases: the static phase, which is executed offline and in advance with respect to the delivery day, and the dynamic phase, which is executed in real-time to cope with unexpected events during the delivery. For the first phase, a matheuristic approach is defined to efficiently solve the combined vehicle routing and loading problems. Differently, for the second phase, a genetic algorithm is proposed to re-route vehicles in real-time, considering both the redefinition in real-time of the nominal trip and/or of the sequence of the customers to be visited. The algorithm is tested both on a literature benchmark and on a real dataset provided by an Italian logistics company. The obtained results show that, on the one hand, the proposed algorithm can automatically provide feasible solutions that minimise travel costs, total travelled distance, and empty space on the vehicles; on the other hand, it can ensure in real-time effective re-routing solutions in case of unexpected events occurring during delivery. Note to Practitioners—This work is motivated by the need for facilitating the operations of planning and routing deliveries in the external logistics sector. We propose an algorithm that automatically generates feasible routing and loading plans for a set of Transport Units (TUs) (i.e., the static phase), and then updates in real-time the nominal route in case of unexpected events (i.e., the dynamic phase). More specifically, the first phase of the algorithm takes as input the set of different clients, the list of products packed into bins (i.e., standard packing units) to be delivered to each client, and the set of transport units available for the deliveries, and provides as output the number and type of TUs to be used, the composition of the bins in each transport unit, and the corresponding route, while optimising the space occupation in each TU and the travel costs. The second phase, instead, takes as input the nominal routes computed in the first phase and, in case of unexpected events (e.g., accidents, slowdowns, etc.) affecting one or more routes, it re-routes the involved trucks guaranteeing the maximum efficiency in regards to travel cost, travel time, and quality of service. The adoption of this algorithm by logistic companies supports the automation of the delivery process and drastically improves the efficiency of logistic operations, with particular regard to the number of used TUs, costs, safety of goods, and customers’ satisfaction. IEEE},
  author_keywords = {Container loading; Costs; dynamic vehicle routing; genetic algorithm; Heuristic algorithms; Logistics; logistics 4.0; matheuristics; Planning; Real-time systems; Vehicle dynamics; Vehicle routing},
  keywords = {Costs; Heuristic algorithms; Interactive computer systems; Loading; Real time systems; Routing algorithms; Traffic congestion; Vehicle routing; Vehicles; Container loading; Dynamic Vehicle Routing; Heuristics algorithm; Logistic 4.0; Matheuristic; Real - Time system; Real- time; Transport units; Unexpected events; Vehicle's dynamics; Genetic algorithms},
  type = {Article},
  publication_stage = {Article in press},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Mignoni, N., Martinez-Piazuelo, J., Carli, R., Ocampo-Martinez, C., Quijano, N. & Dotoli, M. (2024) A Game-Theoretical Control Framework for Transactive Energy Trading in Energy Communities IN 2024 European Control Conference, ECC 2024., 786 – 791. doi:10.23919/ECC64448.2024.10591157
  [BibTeX] [Abstract] [Download PDF]

  Under the umbrella of non-cooperative game theory, we formulate a transactive energy framework to model and control energy communities comprised of heterogeneous agents including (yet not limited to) prosumers, energy storage systems, and energy retailers. The underlying control task is defined as a generalized Nash equilibrium problem (GNEP), which must be solved in a distributed fashion. To solve the GNEP, we formulate a Gauss-Seidel-type alternating direction method of multipliers algorithm, which is guaranteed to converge under strongly monotone pseudo-gradient mappings. As such, we provide sufficient conditions on the private cost and energy pricing functions of the community members, so that the strong monotonicity of the overall pseudo-gradient is ensured. Finally, the proposed framework and the effectiveness of the solution method are illustrated through a numerical simulation. © 2024 EUCA.

  @CONFERENCE{Mignoni2024786,
  author = {Mignoni, Nicola and Martinez-Piazuelo, Juan and Carli, Raffaele and Ocampo-Martinez, Carlos and Quijano, Nicanor and Dotoli, Mariagrazia},
  title = {A Game-Theoretical Control Framework for Transactive Energy Trading in Energy Communities},
  year = {2024},
  journal = {2024 European Control Conference, ECC 2024},
  pages = {786 – 791},
  doi = {10.23919/ECC64448.2024.10591157},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200567031&doi=10.23919%2fECC64448.2024.10591157&partnerID=40&md5=940a89b8b7a2b8a90d241be8bd443e4b},
  abstract = {Under the umbrella of non-cooperative game theory, we formulate a transactive energy framework to model and control energy communities comprised of heterogeneous agents including (yet not limited to) prosumers, energy storage systems, and energy retailers. The underlying control task is defined as a generalized Nash equilibrium problem (GNEP), which must be solved in a distributed fashion. To solve the GNEP, we formulate a Gauss-Seidel-type alternating direction method of multipliers algorithm, which is guaranteed to converge under strongly monotone pseudo-gradient mappings. As such, we provide sufficient conditions on the private cost and energy pricing functions of the community members, so that the strong monotonicity of the overall pseudo-gradient is ensured. Finally, the proposed framework and the effectiveness of the solution method are illustrated through a numerical simulation. © 2024 EUCA.},
  keywords = {Game theory; Power markets; Control energy; Control framework; Energy; Energy trading; Generalized Nash equilibrium problems; Heterogeneous agents; Modelling and controls; Non-cooperative game theory; Pseudo gradients; Storage energy; Numerical methods},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Ajmi, F., Ajmi, F., Ben Othman, S., Zgaya-Biau, H., Dotoli, M., Renard, J. & Hammadi, S. (2024) Real time patient scheduling orchestration for improving key performance indicators in a hospital emergency department. IN Journal of Computational Science, 82.. doi:10.1016/j.jocs.2024.102422
  [BibTeX] [Abstract] [Download PDF]

  Healthcare systems worldwide are increasingly subject to in-depth analysis. Problems in healthcare systems are of concern to the general public. For example, overcrowding in emergency departments creates several issues including longer waiting times, more frequent medical errors, a longer length of stay and worsened performance indicators. Overcrowding situations reduce the availability of staff and material resources, and therefore deteriorate the quality of care. The main cause of the overcrowding in emergency departments is the permanent interferences between the scheduled patients, unscheduled patients and urgent and unscheduled patients arriving at the emergency department. The objective of the present study is to develop an innovative decision support system that minimizes these interferences, while taking into account the perturbations that can occur throughout the day. The research’s ultimate goal is to improve the performance indicators via two processes: the first is a memetic algorithm based on a four dimensional hypercube genetic algorithm and local search techniques, and the second is based on a multi-agent system which dynamically orchestrates the patient pathway (given by the scheduling algorithm). In order to test and validate our approach, experiments are designed with real data from the adult emergency department at Lille University Medical Center. Simulations showed that with our approach we were able to reduce the waiting time of patients by 28.12%. © 2024 Elsevier B.V.

  @ARTICLE{Ajmi2024,
  author = {Ajmi, Faiza and Ajmi, Faten and Ben Othman, Sarah and Zgaya-Biau, Hayfa and Dotoli, Mariagrazia and Renard, Jean-Marie and Hammadi, Slim},
  title = {Real time patient scheduling orchestration for improving key performance indicators in a hospital emergency department},
  year = {2024},
  journal = {Journal of Computational Science},
  volume = {82},
  doi = {10.1016/j.jocs.2024.102422},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201883498&doi=10.1016%2fj.jocs.2024.102422&partnerID=40&md5=e68ef866b2f6dd914e1151a64cb430fc},
  abstract = {Healthcare systems worldwide are increasingly subject to in-depth analysis. Problems in healthcare systems are of concern to the general public. For example, overcrowding in emergency departments creates several issues including longer waiting times, more frequent medical errors, a longer length of stay and worsened performance indicators. Overcrowding situations reduce the availability of staff and material resources, and therefore deteriorate the quality of care. The main cause of the overcrowding in emergency departments is the permanent interferences between the scheduled patients, unscheduled patients and urgent and unscheduled patients arriving at the emergency department. The objective of the present study is to develop an innovative decision support system that minimizes these interferences, while taking into account the perturbations that can occur throughout the day. The research's ultimate goal is to improve the performance indicators via two processes: the first is a memetic algorithm based on a four dimensional hypercube genetic algorithm and local search techniques, and the second is based on a multi-agent system which dynamically orchestrates the patient pathway (given by the scheduling algorithm). In order to test and validate our approach, experiments are designed with real data from the adult emergency department at Lille University Medical Center. Simulations showed that with our approach we were able to reduce the waiting time of patients by 28.12%. © 2024 Elsevier B.V.},
  author_keywords = {Dynamic scheduling; Emergency department; Four dimensional hypercube algorithm; Memetic algorithm; Multi-agent system; Orchestration},
  keywords = {Genetic algorithms; Multi agent systems; Dynamic scheduling; Emergency departments; Four dimensional hypercube algorithm; Healthcare systems; Hyper-cubes; Memetic algorithms; Multiagent systems (MASs); Orchestration; Performance indicators; Waiting time; Scheduling algorithms},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Zhukovskii, K., Ovsiannikova, P., Jhunjhunwala, P., Scarabaggio, P., Carli, R., Dotoli, M. & Vyatkin, V. (2024) Energy Consumption Optimisation for Horticultural Facilities IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA.. doi:10.1109/ETFA61755.2024.10710757
  [BibTeX] [Abstract] [Download PDF]

  This paper proposes a framework designed to optimise energy consumption in vertical farming. It aims to maximise cost efficiency by balancing between minimising system operations during the electricity price peaks and the ability to trade capacity on the FCR market while also fulfilling constraints on the internal growing process. We consider that the vertical farming system has distributed control with a series of actuators controlled by various spatially distributed PLCs that we refer to as agents, to underline their independence. The paper conducts two experiments for a lO-agent system with a Pareto controller and a lOO-agent system with a Lagrangian approach and shows the balance between more cost-efficient momentary energy consumption control. © 2024 IEEE.

  @CONFERENCE{Zhukovskii2024,
  author = {Zhukovskii, Kirill and Ovsiannikova, Polina and Jhunjhunwala, Pranay and Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia and Vyatkin, Valeriy},
  title = {Energy Consumption Optimisation for Horticultural Facilities},
  year = {2024},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  doi = {10.1109/ETFA61755.2024.10710757},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207826602&doi=10.1109%2fETFA61755.2024.10710757&partnerID=40&md5=301035e618ab242689424422b21164c4},
  abstract = {This paper proposes a framework designed to optimise energy consumption in vertical farming. It aims to maximise cost efficiency by balancing between minimising system operations during the electricity price peaks and the ability to trade capacity on the FCR market while also fulfilling constraints on the internal growing process. We consider that the vertical farming system has distributed control with a series of actuators controlled by various spatially distributed PLCs that we refer to as agents, to underline their independence. The paper conducts two experiments for a lO-agent system with a Pareto controller and a lOO-agent system with a Lagrangian approach and shows the balance between more cost-efficient momentary energy consumption control. © 2024 IEEE.},
  author_keywords = {energy consumption optimisation; multi-agent systems; vertical farming},
  keywords = {Agent systems; Cost-efficiency; Electricity prices; Energy consumption optimization; Energy-consumption; Farming system; Growing process; Multiagent systems (MASs); Systems operation; Vertical farming},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

2023

• Mignoni, N., Carli, R. & Dotoli, M. (2023) Layout Optimization for Photovoltaic Panels in Solar Power Plants via a MINLP Approach. IN IEEE Transactions on Automation Science and Engineering, .1–14. doi:10.1109/TASE.2023.3322786
  [BibTeX] [Abstract] [Download PDF]

  Photovoltaic (PV) technology is one of the most popular means of renewable generation, whose applications range from commercial and residential buildings to industrial facilities and grid infrastructures. The problem of determining a suitable layout for the PV arrays, on a given deployment region, is generally non-trivial and has a crucial importance in the planning phase of solar plants design and development. In this paper, we provide a mixed integer non-linear programming formulation of the PV arrays’ layout problem. First, we define the astronomical and geometrical models, considering crucial factors such as self-shadowing and irradiance variability, depending on the geographical position of the solar plant and yearly time window. Subsequently, we formalize the mathematical optimization problem, whose constraints’ set is characterized by non-convexities. In order to propose a computationally tractable approach, we provide a tight parametrized convex relaxation. The resulting optimization resolution procedure is tested numerically, using realistic data, and benchmarked against the traditional global resolution approach, showing that the proposed methodology yields near-optimal solutions in lower computational time. Note to Practitioners—The paper is motivated by the need for efficient algorithmic procedures which can yield near-optimal solutions to the PV arrays layout problem. Due to the strong non-convexity of even simple instances, the existing methods heavily rely on global or stochastic solvers, which are computationally demanding, both in terms of resources and run-time. Our approach acts as a baseline, from which practitioners can derive more elaborate instances, by suitably modifying both the objective function and/or the constraints. In fact, we focus on the minimum set of necessary geometrical (e.g., arrays position model), astronomical (e.g., irradiance variation), and operational (e.g., power requirements) constraints which make the overall problem hard. The Appendices provide a guideline for suitably choosing the optimization parameters. All data and simulation code are available on a public repository at: https://github.com/nicomignoni/pvlayout.git. Authors

  @ARTICLE{Mignoni20231,
  author = {Mignoni, Nicola and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Layout Optimization for Photovoltaic Panels in Solar Power Plants via a MINLP Approach},
  year = {2023},
  journal = {IEEE Transactions on Automation Science and Engineering},
  pages = {1–14},
  doi = {10.1109/TASE.2023.3322786},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181574361&doi=10.1109%2fTASE.2023.3322786&partnerID=40&md5=81a2752bb7efb922f17af8b437e4693b},
  abstract = {Photovoltaic (PV) technology is one of the most popular means of renewable generation, whose applications range from commercial and residential buildings to industrial facilities and grid infrastructures. The problem of determining a suitable layout for the PV arrays, on a given deployment region, is generally non-trivial and has a crucial importance in the planning phase of solar plants design and development. In this paper, we provide a mixed integer non-linear programming formulation of the PV arrays’ layout problem. First, we define the astronomical and geometrical models, considering crucial factors such as self-shadowing and irradiance variability, depending on the geographical position of the solar plant and yearly time window. Subsequently, we formalize the mathematical optimization problem, whose constraints’ set is characterized by non-convexities. In order to propose a computationally tractable approach, we provide a tight parametrized convex relaxation. The resulting optimization resolution procedure is tested numerically, using realistic data, and benchmarked against the traditional global resolution approach, showing that the proposed methodology yields near-optimal solutions in lower computational time. Note to Practitioners—The paper is motivated by the need for efficient algorithmic procedures which can yield near-optimal solutions to the PV arrays layout problem. Due to the strong non-convexity of even simple instances, the existing methods heavily rely on global or stochastic solvers, which are computationally demanding, both in terms of resources and run-time. Our approach acts as a baseline, from which practitioners can derive more elaborate instances, by suitably modifying both the objective function and/or the constraints. In fact, we focus on the minimum set of necessary geometrical (e.g., arrays position model), astronomical (e.g., irradiance variation), and operational (e.g., power requirements) constraints which make the overall problem hard. The Appendices provide a guideline for suitably choosing the optimization parameters. All data and simulation code are available on a public repository at: https://github.com/nicomignoni/pvlayout.git. Authors},
  author_keywords = {Azimuth; convexification; Layout; Mathematical models; mixed integer non-linear programming; non-convex optimization; Observers; Optimization; parametrization; Photovoltaic; Photovoltaic systems; solar array layout; solar power plants; Sun},
  keywords = {Convex optimization; Integer programming; Nonlinear programming; Optimal systems; Relaxation processes; Solar energy; Solar panels; Solar power generation; Stochastic systems; Array layout; Azimuth; Convexification; Layout; Mixed-integer nonlinear programming; Nonconvex optimization; Observer; Optimisations; Parametrizations; Photovoltaic systems; Photovoltaics; Solar array layout; Solar arrays; Solar power plants},
  type = {Article},
  publication_stage = {Article in press},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Green Open Access, Hybrid Gold Open Access}
  }

• Mignoni, N., Carli, R. & Dotoli, M. (2023) A Noncooperative Stochastic Rolling Horizon Control Framework for V1G and V2B Scheduling in Energy Communities IN 2023 European Control Conference, ECC 2023.. doi:10.23919/ECC57647.2023.10178202
  [BibTeX] [Abstract] [Download PDF]

  In this paper, we propose a novel control strategy for the optimal scheduling of an energy community constituted by prosumers and equipped with unidirectional vehicle-to-grid (V1G) and vehicle-to-building (V2B) capabilities. In particular, V2B services are provided by long-term parked electric vehicles (EVs) thus acting as temporary storage systems by prosumers, which in turn offer the V1G service to EVs provisionally plugged into charging stations. To tackle the stochastic nature of the framework, we assume that EVs communicate their parking and recharging time distribution to prosumers, allowing them to improve their energy allocation. Prosumers and EVs interact in a rolling horizon control framework with the aim of achieving an agreement on their operating strategies. The resulting control problem is formulated as a generalized Nash equilibrium problem, addressed through the variational inequality theory, and solved in a distributed fashion leveraging on the accelerated distributed augmented Lagrangian method (ADALM). The convergence and effectiveness of the proposed approach are validated through numerical simulations under realistic scenarios. © 2023 EUCA.

  @CONFERENCE{Mignoni2023,
  author = {Mignoni, Nicola and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A Noncooperative Stochastic Rolling Horizon Control Framework for V1G and V2B Scheduling in Energy Communities},
  year = {2023},
  journal = {2023 European Control Conference, ECC 2023},
  doi = {10.23919/ECC57647.2023.10178202},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166479889&doi=10.23919%2fECC57647.2023.10178202&partnerID=40&md5=e34ca4551ecbe785858f9937e0c0a38c},
  abstract = {In this paper, we propose a novel control strategy for the optimal scheduling of an energy community constituted by prosumers and equipped with unidirectional vehicle-to-grid (V1G) and vehicle-to-building (V2B) capabilities. In particular, V2B services are provided by long-term parked electric vehicles (EVs) thus acting as temporary storage systems by prosumers, which in turn offer the V1G service to EVs provisionally plugged into charging stations. To tackle the stochastic nature of the framework, we assume that EVs communicate their parking and recharging time distribution to prosumers, allowing them to improve their energy allocation. Prosumers and EVs interact in a rolling horizon control framework with the aim of achieving an agreement on their operating strategies. The resulting control problem is formulated as a generalized Nash equilibrium problem, addressed through the variational inequality theory, and solved in a distributed fashion leveraging on the accelerated distributed augmented Lagrangian method (ADALM). The convergence and effectiveness of the proposed approach are validated through numerical simulations under realistic scenarios. © 2023 EUCA.},
  keywords = {Lagrange multipliers; Stochastic systems; Variational techniques; Vehicle-to-grid; Vehicles; Control framework; Control strategies; Energy; Horizon control; Optimal scheduling; Rolling horizon; Stochastics; Temporary storage; Unidirectional vehicles; Vehicle to grids; Constrained optimization},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Mignoni, N., Carli, R. & Dotoli, M. (2023) Distributed Noncooperative MPC for Energy Scheduling of Charging and Trading Electric Vehicles in Energy Communities. IN IEEE Transactions on Control Systems Technology, 31.2159 – 2172. doi:10.1109/TCST.2023.3291549
  [BibTeX] [Abstract] [Download PDF]

  In this article, we propose a novel control strategy for the optimal scheduling of an energy community (EC) constituted by prosumers and equipped with unidirectional vehicle-to-grid (V1G) and vehicle-to-building (V2B) capabilities. In particular, V2B services are provided by long-term parked electric vehicles (EVs), used as temporary storage systems by prosumers, who in turn offer the V1G service to EVs provisionally plugged into charging stations. To tackle the stochastic nature of the framework, we assume that EVs communicate their parking and recharging time distribution to prosumers, allowing them to improve the energy allocation process. Acting as selfish agents, prosumers and EVs interact in a rolling horizon control framework with the aim of achieving an agreement on their operating strategies. The resulting control problem is formulated as a generalized Nash equilibrium (NE) problem, addressed through the variational inequality (VI) theory, and solved in a distributed fashion leveraging on the accelerated distributed augmented Lagrangian method (ADALM), showing sufficient conditions for guaranteeing convergence. The proposed model predictive control (MPC) approach is validated through numerical simulations under realistic scenarios. © 1993-2012 IEEE.

  @ARTICLE{Mignoni20232159,
  author = {Mignoni, Nicola and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Distributed Noncooperative MPC for Energy Scheduling of Charging and Trading Electric Vehicles in Energy Communities},
  year = {2023},
  journal = {IEEE Transactions on Control Systems Technology},
  volume = {31},
  number = {5},
  pages = {2159 – 2172},
  doi = {10.1109/TCST.2023.3291549},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165268827&doi=10.1109%2fTCST.2023.3291549&partnerID=40&md5=a1747e82483205009749a103f96f0f12},
  abstract = {In this article, we propose a novel control strategy for the optimal scheduling of an energy community (EC) constituted by prosumers and equipped with unidirectional vehicle-to-grid (V1G) and vehicle-to-building (V2B) capabilities. In particular, V2B services are provided by long-term parked electric vehicles (EVs), used as temporary storage systems by prosumers, who in turn offer the V1G service to EVs provisionally plugged into charging stations. To tackle the stochastic nature of the framework, we assume that EVs communicate their parking and recharging time distribution to prosumers, allowing them to improve the energy allocation process. Acting as selfish agents, prosumers and EVs interact in a rolling horizon control framework with the aim of achieving an agreement on their operating strategies. The resulting control problem is formulated as a generalized Nash equilibrium (NE) problem, addressed through the variational inequality (VI) theory, and solved in a distributed fashion leveraging on the accelerated distributed augmented Lagrangian method (ADALM), showing sufficient conditions for guaranteeing convergence. The proposed model predictive control (MPC) approach is validated through numerical simulations under realistic scenarios. © 1993-2012 IEEE.},
  author_keywords = {Distributed optimization; electric vehicles (EVs); energy communities (ECs); game theory; model predictive control (MPC); unilateral vehicle-to-grid (V1G); vehicle-to-building (V2B)},
  keywords = {Charging (batteries); Constrained optimization; Electric vehicles; Lagrange multipliers; Model predictive control; Predictive control systems; Random processes; Secondary batteries; Stochastic control systems; Stochastic models; Stochastic systems; Variational techniques; Vehicle-to-grid; Battery; Distributed optimization; Electric vehicle; Energy; Energy community; Game; Microgrid; Model predictive control; Model-predictive control; Symmetric matrices; Uncertainty; Unilateral vehicle-to-grid (V1G); Vehicle to grids; Vehicle-to-building (V2B); Game theory},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 13; All Open Access, Green Open Access, Hybrid Gold Open Access}
  }

• Mignoni, N., Scarabaggio, P., Carli, R. & Dotoli, M. (2023) Control frameworks for transactive energy storage services in energy communities. IN Control Engineering Practice, 130.. doi:10.1016/j.conengprac.2022.105364
  [BibTeX] [Abstract] [Download PDF]

  Recently, the decreasing cost of storage technologies and the emergence of economy-driven mechanisms for energy exchange are contributing to the spread of energy communities. In this context, this paper aims at defining innovative transactive control frameworks for energy communities equipped with independent service-oriented energy storage systems. The addressed control problem consists in optimally scheduling the energy activities of a group of prosumers, characterized by their own demand and renewable generation, and a group of energy storage service providers, able to store the prosumers’ energy surplus and, subsequently, release it upon a fee payment. We propose two novel resolution algorithms based on a game theoretical control formulation, a coordinated and an uncoordinated one, which can be alternatively used depending on the underlying communication architecture of the grid. The two proposed approaches are validated through numerical simulations on realistic scenarios. Results show that the use of a particular framework does not alter fairness, at least at the community level, i.e., no participant in the groups of prosumers or providers can strongly benefit from changing its strategy while compromising others’ welfare. Lastly, the approaches are compared with a centralized control method showing better computational results. © 2022 Elsevier Ltd

  @ARTICLE{Mignoni2023,
  author = {Mignoni, Nicola and Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Control frameworks for transactive energy storage services in energy communities},
  year = {2023},
  journal = {Control Engineering Practice},
  volume = {130},
  doi = {10.1016/j.conengprac.2022.105364},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140312671&doi=10.1016%2fj.conengprac.2022.105364&partnerID=40&md5=c2f86f25172d9c67e24d1f09c9b54689},
  abstract = {Recently, the decreasing cost of storage technologies and the emergence of economy-driven mechanisms for energy exchange are contributing to the spread of energy communities. In this context, this paper aims at defining innovative transactive control frameworks for energy communities equipped with independent service-oriented energy storage systems. The addressed control problem consists in optimally scheduling the energy activities of a group of prosumers, characterized by their own demand and renewable generation, and a group of energy storage service providers, able to store the prosumers’ energy surplus and, subsequently, release it upon a fee payment. We propose two novel resolution algorithms based on a game theoretical control formulation, a coordinated and an uncoordinated one, which can be alternatively used depending on the underlying communication architecture of the grid. The two proposed approaches are validated through numerical simulations on realistic scenarios. Results show that the use of a particular framework does not alter fairness, at least at the community level, i.e., no participant in the groups of prosumers or providers can strongly benefit from changing its strategy while compromising others’ welfare. Lastly, the approaches are compared with a centralized control method showing better computational results. © 2022 Elsevier Ltd},
  author_keywords = {Distributed control; Energy communities; Energy storage systems; Game theory; Smart grids; Transactive control; Transactive energy management},
  keywords = {Computation theory; Distributed parameter control systems; Electric power transmission networks; Energy storage; Smart power grids; Control framework; Distributed-control; Energy; Energy community; Energy storage system; Smart grid; Storage services; Storage systems; Transactive controls; Transactive energy management; Game theory},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 30; All Open Access, Green Open Access}
  }

• Proia, S., Cavone, G., Carli, R. & Dotoli, M. (2023) Optimal Control of Drones for a Train-Drone Railway Diagnostic System IN IEEE International Conference on Automation Science and Engineering.. doi:10.1109/CASE56687.2023.10260390
  [BibTeX] [Abstract] [Download PDF]

  The inspection of railway systems with traditional wayside detectors allows mainly the detection of wheels and axle bearings defects and can be time-demanding, unsafe, and heavily dependent on humans. To overcome these issues and then optimize and automate the rail and track diagnosis process, drones can be an excellent solution thanks to their onboard state-of-the-art cameras and sensors. Thus, with the aim of rapidly collecting highly accurate data, an innovative hybrid movable railway diagnostic architecture, consisting of a diagnostic train and a fleet of drones, is defined in this work. From the control point of view, the main interest is in optimally managing the crucial phase of drones returning to and landing on the moving train when the railway inspection mission is completed. To control the fleet of drones, a combination of consensus algorithm in the leader-following mode and linear quadratic regulator (LQR) is implemented for the flight formation phase and the landing phase on the moving base platform (i.e., the diagnostic train), respectively. The landing phase is performed both as vertical or oblique descent through a go to goal and as oblique descent along a predefined path. The obtained results of the railway diagnostic architecture simulations are presented and discussed in detail. In particular, they show that the vertical and oblique descent performed as go to goal are certainly faster than the oblique descent along a predefined path. © 2023 IEEE.

  @CONFERENCE{Proia2023,
  author = {Proia, Silvia and Cavone, Graziana and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Optimal Control of Drones for a Train-Drone Railway Diagnostic System},
  year = {2023},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2023-August},
  doi = {10.1109/CASE56687.2023.10260390},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174392294&doi=10.1109%2fCASE56687.2023.10260390&partnerID=40&md5=e22983c3ba56e013e991d3313a84b33f},
  abstract = {The inspection of railway systems with traditional wayside detectors allows mainly the detection of wheels and axle bearings defects and can be time-demanding, unsafe, and heavily dependent on humans. To overcome these issues and then optimize and automate the rail and track diagnosis process, drones can be an excellent solution thanks to their onboard state-of-the-art cameras and sensors. Thus, with the aim of rapidly collecting highly accurate data, an innovative hybrid movable railway diagnostic architecture, consisting of a diagnostic train and a fleet of drones, is defined in this work. From the control point of view, the main interest is in optimally managing the crucial phase of drones returning to and landing on the moving train when the railway inspection mission is completed. To control the fleet of drones, a combination of consensus algorithm in the leader-following mode and linear quadratic regulator (LQR) is implemented for the flight formation phase and the landing phase on the moving base platform (i.e., the diagnostic train), respectively. The landing phase is performed both as vertical or oblique descent through a go to goal and as oblique descent along a predefined path. The obtained results of the railway diagnostic architecture simulations are presented and discussed in detail. In particular, they show that the vertical and oblique descent performed as go to goal are certainly faster than the oblique descent along a predefined path. © 2023 IEEE.},
  author_keywords = {diagnostics; drone; flight formation; landing; leader following consensus; linear quadratic regulator; quadrotor; Railways},
  keywords = {Landing; Railroads; Rails; Diagnostic; Flight formation; Landing phase; Leader following; Leader following consensus; Linear quadratic; Linear quadratic regulator; Quad rotors; Quadratic regulators; Railway; Drones},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Askari, B., Bozza, A., Cavone, G., Carli, R. & Dotoli, M. (2023) An adaptive constrained clustering approach for real-time fault detection of industrial systems. IN European Journal of Control, 74.. doi:10.1016/j.ejcon.2023.100858
  [BibTeX] [Abstract] [Download PDF]

  Thanks to the pervasive deployment of sensors in Industry 4.0, data-driven methods are recently playing an important role in the fault diagnosis and prognosis of industrial systems. In this paper, a novel Adaptive Constrained Clustering algorithm is defined to support real-time fault detection of an industrial machine, by clustering the incoming monitoring data into two clusters over time, representing the nominal and non-nominal work conditions, respectively. To this aim, the proposed algorithm relies on a two-stage procedure: micro-clustering and constrained macro-clustering. The former stage is responsible for grouping the batches of work-cycle data into micro-clusters, while the data stream continuously arrives from the data acquisition system. Then, after condensing the micro-clusters into vectors of cluster features, and leveraging on additional knowledge on the nominal and non-nominal working conditions (i.e., constraints on some samples), the second stage aims at offline grouping the micro-clusters features into macro-clusters. Experimental results on a real-world industrial case study show that the proposed real time framework achieves the same results of offline baseline methods (e.g., Constrained K-means) with a higher responsiveness and processing speed; in comparison to stream baseline methods (e.g., Stream K-means), the proposed approach obtains more accurate and easily interpretable results. © 2023 European Control Association

  @ARTICLE{Askari2023,
  author = {Askari, Bahman and Bozza, Augusto and Cavone, Graziana and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {An adaptive constrained clustering approach for real-time fault detection of industrial systems},
  year = {2023},
  journal = {European Journal of Control},
  volume = {74},
  doi = {10.1016/j.ejcon.2023.100858},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162877723&doi=10.1016%2fj.ejcon.2023.100858&partnerID=40&md5=e062207fcb506e79c37bedf7a930b430},
  abstract = {Thanks to the pervasive deployment of sensors in Industry 4.0, data-driven methods are recently playing an important role in the fault diagnosis and prognosis of industrial systems. In this paper, a novel Adaptive Constrained Clustering algorithm is defined to support real-time fault detection of an industrial machine, by clustering the incoming monitoring data into two clusters over time, representing the nominal and non-nominal work conditions, respectively. To this aim, the proposed algorithm relies on a two-stage procedure: micro-clustering and constrained macro-clustering. The former stage is responsible for grouping the batches of work-cycle data into micro-clusters, while the data stream continuously arrives from the data acquisition system. Then, after condensing the micro-clusters into vectors of cluster features, and leveraging on additional knowledge on the nominal and non-nominal working conditions (i.e., constraints on some samples), the second stage aims at offline grouping the micro-clusters features into macro-clusters. Experimental results on a real-world industrial case study show that the proposed real time framework achieves the same results of offline baseline methods (e.g., Constrained K-means) with a higher responsiveness and processing speed; in comparison to stream baseline methods (e.g., Stream K-means), the proposed approach obtains more accurate and easily interpretable results. © 2023 European Control Association},
  author_keywords = {Constrained clustering; Fault detection; Industrial systems; Machine learning; Stream clustering; Unsupervised learning},
  keywords = {Data acquisition; K-means clustering; Knowledge management; Real time systems; Unsupervised learning; Cluster feature; Clusterings; Constrained clustering; Faults detection; Industrial systems; Machine-learning; Micro-clusters; Offline; Real time fault detection; Stream clustering; Fault detection},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Dammacco, L., Carli, R., Gattullo, M., Lazazzera, V., Fiorentino, M. & Dotoli, M. (2023) Virtual Golden Zone for Enhancing the Ergonomics of Complex Production Lines. IN Lecture Notes in Mechanical Engineering, .1436 – 1447. doi:10.1007/978-3-031-15928-2_125
  [BibTeX] [Abstract] [Download PDF]

  For the sake of being competitive in an ever-changing market, industrial companies need a redefinition of traditional design and integration of parts, equipment, and services such a redefinition allows effectively addressing the interaction between machines and operators, particularly in the area of complex production lines. In this context, enhancing ergonomics is crucial to reduce fatigue and stress of workers and increase work-place efficiency and comfort. Moreover, identifying ergonomic flaws in three-dimensional human-machine design problems (e.g., body posture, reach, visibility) at an early stage of the engineering process allows to prevent these issues at a low cost. Virtual reality (VR) is emerging as a powerful tool to improve the ergonomic assessment in the design of complex production lines. However, VR is not yet a well-consolidated practice for industrial companies, and the state-of-the-art applications are limited to simplified, isolated, and customized experiments. This work proposes the use of a virtual golden zone (VGZ) as a standard and efficient VR method for the ergonomic analysis and optimization of operator activities in manual manufacturing stations. The resulting effectiveness and benefits are highlighted through the application of the approach to a real industrial case study. Finally, the outcomes of a usability questionnaire, compiled by the professionals involved in the VR reviews, are presented to evaluate the usability of the VGZ methodology in the design process of complex production lines. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

  @ARTICLE{Dammacco20231436,
  author = {Dammacco, Lucilla and Carli, Raffaele and Gattullo, Michele and Lazazzera, Vito and Fiorentino, Michele and Dotoli, Mariagrazia},
  title = {Virtual Golden Zone for Enhancing the Ergonomics of Complex Production Lines},
  year = {2023},
  journal = {Lecture Notes in Mechanical Engineering},
  pages = {1436 – 1447},
  doi = {10.1007/978-3-031-15928-2_125},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140467887&doi=10.1007%2f978-3-031-15928-2_125&partnerID=40&md5=b6846c4969dd54de6bdc98c21de2c979},
  abstract = {For the sake of being competitive in an ever-changing market, industrial companies need a redefinition of traditional design and integration of parts, equipment, and services such a redefinition allows effectively addressing the interaction between machines and operators, particularly in the area of complex production lines. In this context, enhancing ergonomics is crucial to reduce fatigue and stress of workers and increase work-place efficiency and comfort. Moreover, identifying ergonomic flaws in three-dimensional human-machine design problems (e.g., body posture, reach, visibility) at an early stage of the engineering process allows to prevent these issues at a low cost. Virtual reality (VR) is emerging as a powerful tool to improve the ergonomic assessment in the design of complex production lines. However, VR is not yet a well-consolidated practice for industrial companies, and the state-of-the-art applications are limited to simplified, isolated, and customized experiments. This work proposes the use of a virtual golden zone (VGZ) as a standard and efficient VR method for the ergonomic analysis and optimization of operator activities in manual manufacturing stations. The resulting effectiveness and benefits are highlighted through the application of the approach to a real industrial case study. Finally, the outcomes of a usability questionnaire, compiled by the professionals involved in the VR reviews, are presented to evaluate the usability of the VGZ methodology in the design process of complex production lines. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
  author_keywords = {Complex production lines; Ergonomics; Human computer interaction; Virtual reality},
  keywords = {Cost engineering; Ergonomics; Human computer interaction; Machine design; Body postures; Complex production; Complex production line; Design and integrations; Design problems; Human-machine; Industrial companies; Production line; Work place; Workers'; Virtual reality},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Askari, B., Cavone, G., Carli, R., Grall, A. & Dotoli, M. (2023) A Semi-Supervised Learning Approach for Fault Detection and Diagnosis in Complex Mechanical Systems IN IEEE International Conference on Automation Science and Engineering.. doi:10.1109/CASE56687.2023.10260469
  [BibTeX] [Abstract] [Download PDF]

  The integration of artificial intelligence in mechanical fault detection and diagnosis (FDD) helps to increase reliability, reduce costs, and improve the overall performance of mechanical systems in Industry 4.0 applications. Most interesting industrial applications nowadays come from dynamic environments where data are generated continuously over time and where the labeled data are scarce and expensive. Therefore, semi-supervised learning (SSL) can be particularly useful in FDD because faults may be rare or difficult to identify, and may not be fully represented in the labeled data. By using a combination of labeled and unlabeled data, SSL can help to identify these rare or difficult-to-detect faults, leading to more effective FDD. In this paper, graph-based SSL relying on label propagation is combined with conventional classification algorithms to detect potential failures in complex mechanical systems. Experimental results on realistic pneumatic and hydraulic systems from the related literature show that the proposed method can effectively enlarge the labeled datasets and interestingly identify different types of non-nominal conditions with higher accuracy compared to baseline methodologies. © 2023 IEEE.

  @CONFERENCE{Askari2023,
  author = {Askari, Bahman and Cavone, Graziana and Carli, Raffaele and Grall, Antoine and Dotoli, Mariagrazia},
  title = {A Semi-Supervised Learning Approach for Fault Detection and Diagnosis in Complex Mechanical Systems},
  year = {2023},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2023-August},
  doi = {10.1109/CASE56687.2023.10260469},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174423884&doi=10.1109%2fCASE56687.2023.10260469&partnerID=40&md5=ec89c19b64a796dcd68e955a87b2769a},
  abstract = {The integration of artificial intelligence in mechanical fault detection and diagnosis (FDD) helps to increase reliability, reduce costs, and improve the overall performance of mechanical systems in Industry 4.0 applications. Most interesting industrial applications nowadays come from dynamic environments where data are generated continuously over time and where the labeled data are scarce and expensive. Therefore, semi-supervised learning (SSL) can be particularly useful in FDD because faults may be rare or difficult to identify, and may not be fully represented in the labeled data. By using a combination of labeled and unlabeled data, SSL can help to identify these rare or difficult-to-detect faults, leading to more effective FDD. In this paper, graph-based SSL relying on label propagation is combined with conventional classification algorithms to detect potential failures in complex mechanical systems. Experimental results on realistic pneumatic and hydraulic systems from the related literature show that the proposed method can effectively enlarge the labeled datasets and interestingly identify different types of non-nominal conditions with higher accuracy compared to baseline methodologies. © 2023 IEEE.},
  keywords = {Fault detection; Hydraulic equipment; Learning systems; Complex mechanical system; Dynamic environments; Fault detection and diagnosis; Labeled data; Mechanical faults; Mechanical systems; Performance; Reduce costs; Semi-supervised learning; Supervised learning approaches; Graphic methods},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Mignoni, N., Carli, R. & Dotoli, M. (2023) An Optimization Tool for Displacing Photovoltaic Arrays in Polygonal Areas IN EUROCON 2023 – 20th International Conference on Smart Technologies, Proceedings., 573 – 578. doi:10.1109/EUROCON56442.2023.10198934
  [BibTeX] [Abstract] [Download PDF]

  In this paper, we discuss the problem of optimally designing the layout of a given number of photovoltaic arrays on a flat polygonal surface, in order to maximize a suitable objective function, e.g., the total generated energy. This means finding their optimal position, azimuth and tilt. The considered problem becomes non-trivial when considering effects such as irradiance variability and self-shadowing. We first provide a description of the system model and the associated optimization problem, showing how the resulting formulation presents non-convexities. Then, we provide a tight parametrized convex relaxation, which is computationally tractable and for which optimality conditions hold. We provide numerical simulations using realistic data, showing how the proposed methodology yields near-optimal solutions in lower computational time with respect to the traditional global resolution approach. © 2023 IEEE.

  @CONFERENCE{Mignoni2023573,
  author = {Mignoni, Nicola and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {An Optimization Tool for Displacing Photovoltaic Arrays in Polygonal Areas},
  year = {2023},
  journal = {EUROCON 2023 - 20th International Conference on Smart Technologies, Proceedings},
  pages = {573 – 578},
  doi = {10.1109/EUROCON56442.2023.10198934},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168705720&doi=10.1109%2fEUROCON56442.2023.10198934&partnerID=40&md5=918aa0710a8540e5ce9ea625b0a385d4},
  abstract = {In this paper, we discuss the problem of optimally designing the layout of a given number of photovoltaic arrays on a flat polygonal surface, in order to maximize a suitable objective function, e.g., the total generated energy. This means finding their optimal position, azimuth and tilt. The considered problem becomes non-trivial when considering effects such as irradiance variability and self-shadowing. We first provide a description of the system model and the associated optimization problem, showing how the resulting formulation presents non-convexities. Then, we provide a tight parametrized convex relaxation, which is computationally tractable and for which optimality conditions hold. We provide numerical simulations using realistic data, showing how the proposed methodology yields near-optimal solutions in lower computational time with respect to the traditional global resolution approach. © 2023 IEEE.},
  keywords = {Energy; Non-trivial; Nonconvexity; Objective functions; Optimal position; Optimization problems; Optimization tools; Photovoltaic arrays; Polygonal surface; System models; Relaxation processes},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Proia, S., Cavone, G., Scarabaggio, P., Carli, R. & Dotoli, M. (2023) Safety Compliant, Ergonomic and Time-Optimal Trajectory Planning for Collaborative Robotics. IN IEEE Transactions on Automation Science and Engineering, .1–12. doi:10.1109/TASE.2023.3331505
  [BibTeX] [Abstract] [Download PDF]

  The demand for safe and ergonomic workplaces is rapidly growing in modern industrial scenarios, especially for companies that intensely rely on Human-Robot Collaboration (HRC). This work focuses on optimizing the trajectory of the end-effector of a cobot arm in a collaborative industrial environment, ensuring the maximization of the operator’s safety and ergonomics without sacrificing production efficiency requirements. Hence, a multi-objective optimization strategy for trajectory planning in a safe and ergonomic HRC is defined. This approach aims at finding the best trade-off between the total traversal time of the cobot’s end-effector trajectory and ergonomics for the human worker, while respecting in the kinematic constraint of the optimization problem the ISO safety requirements through the well-known Speed and Separation Monitoring (SSM) methodology. Guaranteeing an ergonomic HRC means reducing musculoskeletal disorders linked to risky and highly repetitive activities. The three main phases of the proposed technique are described as follows. First, a manikin designed using a dedicated software is employed to evaluate the Rapid Upper Limb Assessment (RULA) ergonomic index in the working area. Next, a second-order cone programming problem is defined to represent a time-optimal safety compliant trajectory planning problem. Finally, the trajectory that ensures the best compromise between these two opposing goals –minimizing the task’s traversal time and maintaining a high level of ergonomics for the human worker– is computed by defining and solving a multi-objective control problem. The method is tested on an experimental case study in reference to an assembly task and the obtained results are discussed, showing the effectiveness of the proposed approach. Note to Practitioners—Health and safety in workplaces are business imperatives, since they ensure not only a safe collaboration between industrial machinery and human operators, but also an increased productivity and flexibility of the entire industrial process. Hence, investing in health is a real driver for business growth. The key enabling technologies of Industry 4.0, such as collaborative robotics, exoskeletons, virtual and augmented reality, require standardization and indispensable technical safety requirements that cannot ignore physical, sensory, and psychological peculiarities of the human worker and aspects like usability and acceptability of these technologies in performing their activities. Against this ongoing industrial challenge, the aim of this paper is to provide researchers and practitioners with an innovative HRC trajectory planning methodology focused on enhancing production efficiency while respecting the SSM ISO safety requirement and guaranteeing the ergonomic optimal position of the operator during an assembly task. Therefore, the proposed methodology can be a convenient solution to be deployed in industrial companies, since it can support human operators by drastically reducing work-related musculoskeletal disorders and augmenting their performance in the working environment. Authors

  @ARTICLE{Proia20231,
  author = {Proia, Silvia and Cavone, Graziana and Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Safety Compliant, Ergonomic and Time-Optimal Trajectory Planning for Collaborative Robotics},
  year = {2023},
  journal = {IEEE Transactions on Automation Science and Engineering},
  pages = {1–12},
  doi = {10.1109/TASE.2023.3331505},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178048425&doi=10.1109%2fTASE.2023.3331505&partnerID=40&md5=7fe6504b770617ce6996f3bf55c5d7c1},
  abstract = {The demand for safe and ergonomic workplaces is rapidly growing in modern industrial scenarios, especially for companies that intensely rely on Human-Robot Collaboration (HRC). This work focuses on optimizing the trajectory of the end-effector of a cobot arm in a collaborative industrial environment, ensuring the maximization of the operator’s safety and ergonomics without sacrificing production efficiency requirements. Hence, a multi-objective optimization strategy for trajectory planning in a safe and ergonomic HRC is defined. This approach aims at finding the best trade-off between the total traversal time of the cobot’s end-effector trajectory and ergonomics for the human worker, while respecting in the kinematic constraint of the optimization problem the ISO safety requirements through the well-known Speed and Separation Monitoring (SSM) methodology. Guaranteeing an ergonomic HRC means reducing musculoskeletal disorders linked to risky and highly repetitive activities. The three main phases of the proposed technique are described as follows. First, a manikin designed using a dedicated software is employed to evaluate the Rapid Upper Limb Assessment (RULA) ergonomic index in the working area. Next, a second-order cone programming problem is defined to represent a time-optimal safety compliant trajectory planning problem. Finally, the trajectory that ensures the best compromise between these two opposing goals –minimizing the task’s traversal time and maintaining a high level of ergonomics for the human worker– is computed by defining and solving a multi-objective control problem. The method is tested on an experimental case study in reference to an assembly task and the obtained results are discussed, showing the effectiveness of the proposed approach. Note to Practitioners—Health and safety in workplaces are business imperatives, since they ensure not only a safe collaboration between industrial machinery and human operators, but also an increased productivity and flexibility of the entire industrial process. Hence, investing in health is a real driver for business growth. The key enabling technologies of Industry 4.0, such as collaborative robotics, exoskeletons, virtual and augmented reality, require standardization and indispensable technical safety requirements that cannot ignore physical, sensory, and psychological peculiarities of the human worker and aspects like usability and acceptability of these technologies in performing their activities. Against this ongoing industrial challenge, the aim of this paper is to provide researchers and practitioners with an innovative HRC trajectory planning methodology focused on enhancing production efficiency while respecting the SSM ISO safety requirement and guaranteeing the ergonomic optimal position of the operator during an assembly task. Therefore, the proposed methodology can be a convenient solution to be deployed in industrial companies, since it can support human operators by drastically reducing work-related musculoskeletal disorders and augmenting their performance in the working environment. Authors},
  author_keywords = {cobots; Collaboration; Collaborative robotics; Ergonomics; ergonomics; human-robot collaboration (HRC); Optimization; rapid upper limb assessment (RULA); Robots; safety; Safety; speed and separation monitoring; time-optimal trajectory planning; Trajectory; Trajectory planning},
  keywords = {Accident prevention; Augmented reality; Collaborative robots; Distributed computer systems; Economic and social effects; Ergonomics; Exoskeleton (Robotics); Industrial robots; Multiobjective optimization; Occupational risks; Production efficiency; Robot programming; Virtual reality; Collaboration; Human-robot collaboration; Optimisations; Rapid upper limb assessment; Rapid upper limb assessments; Speed and separation monitoring; Time-optimal trajectory planning; Trajectory Planning; Workers'; Trajectories},
  type = {Article},
  publication_stage = {Article in press},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Hybrid Gold Open Access}
  }

• Prunella, M., Scardigno, R. M., Buongiorno, D., Brunetti, A., Longo, N., Carli, R., Dotoli, M. & Bevilacqua, V. (2023) Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey. IN IEEE Access, 11.43370 – 43423. doi:10.1109/ACCESS.2023.3271748
  [BibTeX] [Abstract] [Download PDF]

  Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted feature extraction, selection, and validation, counted on a combined approach of parameterized image processing algorithms and explicated human knowledge. The outstanding performance of deep learning (DL) for vision systems, in automatically discovering a feature representation suitable for the corresponding task, has exponentially increased the number of scientific articles and commercial products aiming at industrial quality assessment. In such a context, this article reviews more than 220 relevant articles from the related literature published until February 2023, covering the recent consolidation and advances in the field of fully-automatic DL-based surface defects inspection systems, deployed in various industrial applications. The analyzed papers have been classified according to a bi-dimensional taxonomy, that considers both the specific defect recognition task and the employed learning paradigm. The dependency on large and high-quality labeled datasets and the different neural architectures employed to achieve an overall perception of both well-visible and subtle defects, through the supervision of fine or/and coarse data annotations have been assessed. The results of our analysis highlight a growing research interest in defect representation power enrichment, especially by transferring pre-trained layers to an optimized network and by explaining the network decisions to suggest trustworthy retention or rejection of the products being evaluated. © 2013 IEEE.

  @ARTICLE{Prunella202343370,
  author = {Prunella, Michela and Scardigno, Roberto Maria and Buongiorno, Domenico and Brunetti, Antonio and Longo, Nicola and Carli, Raffaele and Dotoli, Mariagrazia and Bevilacqua, Vitoantonio},
  title = {Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey},
  year = {2023},
  journal = {IEEE Access},
  volume = {11},
  pages = {43370 – 43423},
  doi = {10.1109/ACCESS.2023.3271748},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159721935&doi=10.1109%2fACCESS.2023.3271748&partnerID=40&md5=d488df827f296aca24ea29641932e0b3},
  abstract = {Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted feature extraction, selection, and validation, counted on a combined approach of parameterized image processing algorithms and explicated human knowledge. The outstanding performance of deep learning (DL) for vision systems, in automatically discovering a feature representation suitable for the corresponding task, has exponentially increased the number of scientific articles and commercial products aiming at industrial quality assessment. In such a context, this article reviews more than 220 relevant articles from the related literature published until February 2023, covering the recent consolidation and advances in the field of fully-automatic DL-based surface defects inspection systems, deployed in various industrial applications. The analyzed papers have been classified according to a bi-dimensional taxonomy, that considers both the specific defect recognition task and the employed learning paradigm. The dependency on large and high-quality labeled datasets and the different neural architectures employed to achieve an overall perception of both well-visible and subtle defects, through the supervision of fine or/and coarse data annotations have been assessed. The results of our analysis highlight a growing research interest in defect representation power enrichment, especially by transferring pre-trained layers to an optimized network and by explaining the network decisions to suggest trustworthy retention or rejection of the products being evaluated. © 2013 IEEE.},
  author_keywords = {Artificial vision; auto-encoder; automatic recognition; convolutional neural network; deep learning; explainable artificial intelligence; feature attention mechanism; generative-adversarial network; industrial surface defects; transfer learning},
  keywords = {Computer vision; Deep neural networks; Extraction; Generative adversarial networks; Image recognition; Image segmentation; Inspection; Inspection equipment; Network coding; Surface defects; Attention mechanisms; Auto encoders; Automatic recognition; Autonomous system; Convolutional neural network; Deep learning; Explainable artificial intelligence; Feature attention mechanism; Features extraction; Industrial surface defect; Manual; Transfer learning; Feature extraction},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 21; All Open Access, Gold Open Access}
  }

• Proia, S., Cavone, G., Tresca, G., Carli, R. & Dotoli, M. (2023) Automatic Control of Drones’ Missions in a Hybrid Truck-Drone Delivery System IN 9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023., 1477 – 1482. doi:10.1109/CoDIT58514.2023.10284110
  [BibTeX] [Abstract] [Download PDF]

  Last-mile delivery is one of the most discussed problems of the last decade due to the growing importance of e-commerce and the development of Industry 4.0. In particular, this problem regards the delivery of parcels from the warehouse to the final customers. In order to bring efficiency and innovation, in this paper a hybrid delivery architecture is considered, which takes advantage of the combined use of a drone and a truck to perform a sequence of pick-ups and deliveries, and the problem of optimal control of the drones’ missions is addressed. The reference scenario is the smart city where the drone of the hybrid delivery architecture is in charge of three different pick-up and delivery missions: truck to point (i.e., pick-up from the truck and delivery to the customer), point to point (i.e., delivery to a customer and pick-up from the subsequent customer), and point to truck (i.e., reentry from a customer to the truck). From the control point of view, the drone is optimally guided in all the operating modes, i.e., ascent and descent from/to truck mode, free flight mode with/without payload, and descent for pick-up/delivery mode, by a receding horizon linear quadratic regulator (LQR), which is able to manage the drone in the dynamic landing on a movable vehicle and to allow the changing in real time of the landing point on the truck. Simulation results of the truck-drone delivery architecture are presented and discussed in detail, proving the effectiveness of the proposed method. © 2023 IEEE.

  @CONFERENCE{Proia20231477,
  author = {Proia, Silvia and Cavone, Graziana and Tresca, Giulia and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Automatic Control of Drones' Missions in a Hybrid Truck-Drone Delivery System},
  year = {2023},
  journal = {9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023},
  pages = {1477 – 1482},
  doi = {10.1109/CoDIT58514.2023.10284110},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177429627&doi=10.1109%2fCoDIT58514.2023.10284110&partnerID=40&md5=01984a4e3bdb410678f081578de2dd3c},
  abstract = {Last-mile delivery is one of the most discussed problems of the last decade due to the growing importance of e-commerce and the development of Industry 4.0. In particular, this problem regards the delivery of parcels from the warehouse to the final customers. In order to bring efficiency and innovation, in this paper a hybrid delivery architecture is considered, which takes advantage of the combined use of a drone and a truck to perform a sequence of pick-ups and deliveries, and the problem of optimal control of the drones' missions is addressed. The reference scenario is the smart city where the drone of the hybrid delivery architecture is in charge of three different pick-up and delivery missions: truck to point (i.e., pick-up from the truck and delivery to the customer), point to point (i.e., delivery to a customer and pick-up from the subsequent customer), and point to truck (i.e., reentry from a customer to the truck). From the control point of view, the drone is optimally guided in all the operating modes, i.e., ascent and descent from/to truck mode, free flight mode with/without payload, and descent for pick-up/delivery mode, by a receding horizon linear quadratic regulator (LQR), which is able to manage the drone in the dynamic landing on a movable vehicle and to allow the changing in real time of the landing point on the truck. Simulation results of the truck-drone delivery architecture are presented and discussed in detail, proving the effectiveness of the proposed method. © 2023 IEEE.},
  author_keywords = {Aerial robotics; drones; last-mile delivery; receding horizon linear quadratic regulator; trajectory tracking},
  keywords = {Aircraft detection; Antennas; Automation; Drones; Free flight; Pickups; Trucks; Aerial robotics; Delivery architecture; Hybrid delivery; Last mile; Last-mile delivery; Linear quadratic; Quadratic regulators; Receding horizon; Receding horizon linear quadratic regulator; Trajectory-tracking; Sales},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Atrigna, M., Buonanno, A., Carli, R., Cavone, G., Scarabaggio, P., Valenti, M., Graditi, G. & Dotoli, M. (2023) A Machine Learning Approach to Fault Prediction of Power Distribution Grids Under Heatwaves. IN IEEE Transactions on Industry Applications, 59.4835 – 4845. doi:10.1109/TIA.2023.3262230
  [BibTeX] [Abstract] [Download PDF]

  Climate change is increasing the occurrence of the so-called heatwaves with a trend that is expected to worsen in the next years due to global warming. The growing intensity and duration of these extreme weather events are leading to a significant number of power system failures, especially in urban areas. This is drastically affecting the reliability and normal operation of power distribution grids around the world, with high financial costs and huge negative impacts on people’s life. Typically, the response to these failure events is approached by post-event analysis, aimed at identifying the grid areas that require resources to increase the resilience of the system and prevent future outages. Nevertheless, understanding the nature of heatwaves and forecasting their impact on power distribution systems can be useful to anticipate them and accelerate a reaction, possibly avoiding negative impacts on power systems and customers. In this study, a structured method to predict distribution grid disruptions caused by heatwaves is defined. The proposed method relies on machine learning to analyze previous failure data and forecast power grid outages using operational and meteorological information. The method is evaluated using real failure data from a large power distribution network located in southern Italy. © 1972-2012 IEEE.

  @ARTICLE{Atrigna20234835,
  author = {Atrigna, Mauro and Buonanno, Amedeo and Carli, Raffaele and Cavone, Graziana and Scarabaggio, Paolo and Valenti, Maria and Graditi, Giorgio and Dotoli, Mariagrazia},
  title = {A Machine Learning Approach to Fault Prediction of Power Distribution Grids Under Heatwaves},
  year = {2023},
  journal = {IEEE Transactions on Industry Applications},
  volume = {59},
  number = {4},
  pages = {4835 – 4845},
  doi = {10.1109/TIA.2023.3262230},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151511272&doi=10.1109%2fTIA.2023.3262230&partnerID=40&md5=89991feff02c7dffe5f98c9f90e0be87},
  abstract = {Climate change is increasing the occurrence of the so-called heatwaves with a trend that is expected to worsen in the next years due to global warming. The growing intensity and duration of these extreme weather events are leading to a significant number of power system failures, especially in urban areas. This is drastically affecting the reliability and normal operation of power distribution grids around the world, with high financial costs and huge negative impacts on people's life. Typically, the response to these failure events is approached by post-event analysis, aimed at identifying the grid areas that require resources to increase the resilience of the system and prevent future outages. Nevertheless, understanding the nature of heatwaves and forecasting their impact on power distribution systems can be useful to anticipate them and accelerate a reaction, possibly avoiding negative impacts on power systems and customers. In this study, a structured method to predict distribution grid disruptions caused by heatwaves is defined. The proposed method relies on machine learning to analyze previous failure data and forecast power grid outages using operational and meteorological information. The method is evaluated using real failure data from a large power distribution network located in southern Italy. © 1972-2012 IEEE.},
  author_keywords = {condition monitoring; fault prediction; heatwaves; machine learning; power system failures; Power system reliability},
  keywords = {Artificial intelligence; Forecasting; Global warming; Learning systems; Outages; Fault prediction; Heating system; Heatwaves; Machine-learning; Power; Power cables; Power system; Power system failures; Power systems reliability; Resilience; Condition monitoring},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 13}
  }

• Bozza, A., Cavone, G., Carli, R. & Dotoli, M. (2023) A Power Electronic Converters-Inspired Approach for Modeling PWM Switched-Based Nonlinear Hydraulic Servo Actuators IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 2477 – 2482. doi:10.1109/SMC53992.2023.10394065
  [BibTeX] [Abstract] [Download PDF]

  This paper investigates a novel approach for properly modeling Hydraulic Servo Actuators (HSAs) based on ON-OFF switching valves. HSAs represent very high efficiency and small size-to-power ratio hydraulic actuators. Their functioning is guaranteed by their control system that ensures the desired flow-rate, and consequently, the proper pressure, to be provided to the actuator’s chambers. Nevertheless, achieving a good model of such HSAs for control purposes is non-trivial, due to their hybrid nature inherited from the switching between the different operating modes produced by valves. To overcome this limit, we propose an average equivalent discrete-time model of the chambers’ pressure dynamics related to a single control input for the digital valves. The proposed model takes inspiration from the analogy existing between hydraulic systems and power electronic converters, and guarantees the same performance as the traditional model, with the advantage of greatly simplifying the control of the servo actuator. Finally, the consistency of the proposed model with respect to its nonlinear hybrid version is proved via numerical examples. © 2023 IEEE.

  @CONFERENCE{Bozza20232477,
  author = {Bozza, Augusto and Cavone, Graziana and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A Power Electronic Converters-Inspired Approach for Modeling PWM Switched-Based Nonlinear Hydraulic Servo Actuators},
  year = {2023},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  pages = {2477 – 2482},
  doi = {10.1109/SMC53992.2023.10394065},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187260571&doi=10.1109%2fSMC53992.2023.10394065&partnerID=40&md5=ba0c9a7b491927b01db552a62bd2d7de},
  abstract = {This paper investigates a novel approach for properly modeling Hydraulic Servo Actuators (HSAs) based on ON-OFF switching valves. HSAs represent very high efficiency and small size-to-power ratio hydraulic actuators. Their functioning is guaranteed by their control system that ensures the desired flow-rate, and consequently, the proper pressure, to be provided to the actuator's chambers. Nevertheless, achieving a good model of such HSAs for control purposes is non-trivial, due to their hybrid nature inherited from the switching between the different operating modes produced by valves. To overcome this limit, we propose an average equivalent discrete-time model of the chambers' pressure dynamics related to a single control input for the digital valves. The proposed model takes inspiration from the analogy existing between hydraulic systems and power electronic converters, and guarantees the same performance as the traditional model, with the advantage of greatly simplifying the control of the servo actuator. Finally, the consistency of the proposed model with respect to its nonlinear hybrid version is proved via numerical examples. © 2023 IEEE.},
  author_keywords = {Electro-Hydraulic Analogy; Hybrid Systems; Hydraulic Servo Actuators; Nonlinear Systems; Pulse Width Modulation (PWM); Switching Systems},
  keywords = {Hydraulic actuators; Hydraulic equipment; Power converters; Power electronics; Pulse width modulation; Switching systems; Control purpose; Electro-hydraulic analogy; Electro-hydraulics; Higher efficiency; Hydraulic servo actuator; Non-trivial; Power electronics converters; Power ratio; Pulse width modulation; Pulsewidth modulations (PWM); Hybrid systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Cavone, G., Stella, S., Scarabaggio, P., Carli, R., Lisi, S., Garavelli, A. C. & Dotoli, M. (2023) A Colored Petri Net Tool for the Design of Robotic Palletizing Cells IN 9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023., 12 – 17. doi:10.1109/CoDIT58514.2023.10284186
  [BibTeX] [Abstract] [Download PDF]

  Driven by the digital transformation required by Logistics 4.0, the use of automation in warehouses is constantly growing. In particular, robotic palletizers offer significant potential for optimizing warehouse operations, thanks to higher flexibility and throughput than traditional palletizing systems. Despite the availability of several solutions in the market, the optimal deployment of a robotic palletizer in warehouses is not straightforward: a design phase is needed to determine the most convenient configuration that ensures automatic palletizing is fully integrated into the warehouse processes. In this paper, we propose a simulation-based versatile tool for modeling and analysis purposes, aimed at supporting the design of a robotic palletizing cell in a bottom-up fashion. As a core methodology, we employ timed colored Petri nets, which allow – once the analysis on packing requirements and constraints is conducted – to rapidly model the system as a composition of basic subsystems, and implement alternative simulations to evaluate the corresponding performance and effectively benchmark the alternative configurations. The proposed approach is applied to a real case study, showing its effectiveness in identifying the solution that achieves a good compromise between the use of resources and the performance of warehouse operations. © 2023 IEEE.

  @CONFERENCE{Cavone202312,
  author = {Cavone, Graziana and Stella, Silvia and Scarabaggio, Paolo and Carli, Raffaele and Lisi, Stefano and Garavelli, Achille Claudio and Dotoli, Mariagrazia},
  title = {A Colored Petri Net Tool for the Design of Robotic Palletizing Cells},
  year = {2023},
  journal = {9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023},
  pages = {12 – 17},
  doi = {10.1109/CoDIT58514.2023.10284186},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177446511&doi=10.1109%2fCoDIT58514.2023.10284186&partnerID=40&md5=fb1f951ba12c45828607bf01cf994fff},
  abstract = {Driven by the digital transformation required by Logistics 4.0, the use of automation in warehouses is constantly growing. In particular, robotic palletizers offer significant potential for optimizing warehouse operations, thanks to higher flexibility and throughput than traditional palletizing systems. Despite the availability of several solutions in the market, the optimal deployment of a robotic palletizer in warehouses is not straightforward: a design phase is needed to determine the most convenient configuration that ensures automatic palletizing is fully integrated into the warehouse processes. In this paper, we propose a simulation-based versatile tool for modeling and analysis purposes, aimed at supporting the design of a robotic palletizing cell in a bottom-up fashion. As a core methodology, we employ timed colored Petri nets, which allow - once the analysis on packing requirements and constraints is conducted - to rapidly model the system as a composition of basic subsystems, and implement alternative simulations to evaluate the corresponding performance and effectively benchmark the alternative configurations. The proposed approach is applied to a real case study, showing its effectiveness in identifying the solution that achieves a good compromise between the use of resources and the performance of warehouse operations. © 2023 IEEE.},
  author_keywords = {Colored Petri net; Discrete Event Systems; Modeling and Simulation; Robotic Palletizing System},
  keywords = {Benchmarking; Petri nets; Robotics; Warehouses; Colored Petri Nets; Digital transformation; Discrete events systems; High-throughput; Model and simulation; Performance; Robotic palletizers; Robotic palletizing system; Robotic-palletizing cell; Warehouse operation; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Tresca, G., Cavone, G., Carli, R. & Dotoli, M. (2023) A mathematical model for the optimal configuration of automated storage systems with sliding trays IN 2023 European Control Conference, ECC 2023.. doi:10.23919/ECC57647.2023.10178251
  [BibTeX] [Abstract] [Download PDF]

  This work aims at contributing to the advancement of Logistics 4.0, focusing on the management of the storage of goods. The goal is to solve the complex problem of efficiently and rapidly configuring Vertical Lift Modules (VLMs) with sliding trays in automated warehouses. This problem is still barely discussed in the related literature and most contributions mainly focus on the optimization of the VLM throughput instead of trays allocation and respective items configuration. To fill this gap, this work proposes a novel mathematical model that allows to properly represent and solve this complex problem, taking into account practical logistic constraints. The problem is defined as a mixed integer non-linear programming model, which is validated on realistic scenarios. Further, a scalability analysis is performed to evaluate its performance even in complex scenarios. The obtained results demonstrate the effectiveness of the model in defining space efficient configurations in short computation time. © 2023 EUCA.

  @CONFERENCE{Tresca2023,
  author = {Tresca, Giulia and Cavone, Graziana and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A mathematical model for the optimal configuration of automated storage systems with sliding trays},
  year = {2023},
  journal = {2023 European Control Conference, ECC 2023},
  doi = {10.23919/ECC57647.2023.10178251},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166474973&doi=10.23919%2fECC57647.2023.10178251&partnerID=40&md5=7a7e0c93dea4f182cc0bc9d38c8350a3},
  abstract = {This work aims at contributing to the advancement of Logistics 4.0, focusing on the management of the storage of goods. The goal is to solve the complex problem of efficiently and rapidly configuring Vertical Lift Modules (VLMs) with sliding trays in automated warehouses. This problem is still barely discussed in the related literature and most contributions mainly focus on the optimization of the VLM throughput instead of trays allocation and respective items configuration. To fill this gap, this work proposes a novel mathematical model that allows to properly represent and solve this complex problem, taking into account practical logistic constraints. The problem is defined as a mixed integer non-linear programming model, which is validated on realistic scenarios. Further, a scalability analysis is performed to evaluate its performance even in complex scenarios. The obtained results demonstrate the effectiveness of the model in defining space efficient configurations in short computation time. © 2023 EUCA.},
  keywords = {Nonlinear programming; Automated storage; Automated warehouse; Complex problems; Linear programming models; Logistics constraints; Mixed-integer nonlinear programming; Optimisations; Realistic scenario; Storage systems; Vertical lift modules; Integer programming},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

2022

• Scarabaggio, P., Carli, R., Parisio, A. & Dotoli, M. (2022) On Controlling Battery Degradation in Vehicle-to-Grid Energy Markets IN IEEE International Conference on Automation Science and Engineering., 1206 – 1211. doi:10.1109/CASE49997.2022.9926729
  [BibTeX] [Abstract] [Download PDF]

  Nowadays, power grids are facing reduced total system inertia as traditional generators are phased out in favor of renewable energy sources. This issue is expected to deepen with the increasing penetration of electric vehicles (EVs). The influence of a single EV on power networks is low; nevertheless, the aggregate impact becomes relevant when they are properly coordinated. In this context, we consider the frequent case of a group of EVs connected to a parking lot with a photovoltaic facility. We propose a novel strategy to optimally control their batteries during the parking session, which is able to satisfy their requirements and energy constraints. EVs participate in a noncooperative energy market based on a smart pricing mechanism that is designed in order to increase the predictability and flexibility of the aggregate parking load. Differently from the existing contributions, we employ a novel approach to minimize the degradation of batteries. The effectiveness of the proposed method is validated through numerical experiments based on a real scenario. © 2022 IEEE.

  @CONFERENCE{Scarabaggio20221206,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Parisio, Alessandra and Dotoli, Mariagrazia},
  title = {On Controlling Battery Degradation in Vehicle-to-Grid Energy Markets},
  year = {2022},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2022-August},
  pages = {1206 – 1211},
  doi = {10.1109/CASE49997.2022.9926729},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141672066&doi=10.1109%2fCASE49997.2022.9926729&partnerID=40&md5=ed24721222037df90795b0e4d7a1cbb1},
  abstract = {Nowadays, power grids are facing reduced total system inertia as traditional generators are phased out in favor of renewable energy sources. This issue is expected to deepen with the increasing penetration of electric vehicles (EVs). The influence of a single EV on power networks is low; nevertheless, the aggregate impact becomes relevant when they are properly coordinated. In this context, we consider the frequent case of a group of EVs connected to a parking lot with a photovoltaic facility. We propose a novel strategy to optimally control their batteries during the parking session, which is able to satisfy their requirements and energy constraints. EVs participate in a noncooperative energy market based on a smart pricing mechanism that is designed in order to increase the predictability and flexibility of the aggregate parking load. Differently from the existing contributions, we employ a novel approach to minimize the degradation of batteries. The effectiveness of the proposed method is validated through numerical experiments based on a real scenario. © 2022 IEEE.},
  author_keywords = {charging scheduling; Electric vehicles; model predictive control},
  keywords = {Aggregates; Charging (batteries); Electric power transmission networks; Electric vehicles; Numerical methods; Renewable energy resources; Secondary batteries; Vehicle-to-grid; Battery degradation; Charging scheduling; Energy markets; Model-predictive control; Parking lots; Power grids; Power networks; Renewable energy source; System inertia; Vehicle to grids; Model predictive control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Mohsen Hosseini, S., Carli, R., Jantzen, J. & Dotoli, M. (2022) Multi-block ADMM Approach for Decentralized Demand Response of Energy Communities with Flexible Loads and Shared Energy Storage System IN 2022 30th Mediterranean Conference on Control and Automation, MED 2022., 67 – 72. doi:10.1109/MED54222.2022.9837173
  [BibTeX] [Abstract] [Download PDF]

  This paper proposes a novel decentralized energy scheduling framework for demand response of energy communities in the case of limited overall capacity of distribution networks. A combined energy scheduling of heating, ventilation, and air conditioning systems and a community energy storage system (CESS) for multiple smart residential users is presented. The proposed approach aims at minimizing the total expected energy costs while ensuring the occupants’ thermal comfort. The optimization problem is first formulated as a mixed-integer linear programming problem, which is converted into a linear programming problem using a tractable approximation method based on a non-complementary charging/discharging strategy of the CESS. The decentralized resolution process is based on multi-block proximal Jacobian alternating direction method of multipliers, ensuring efficient computation and protecting users’ privacy. We assess the effectiveness of the proposed approach through numerical experiments on a realistic case study. © 2022 IEEE.

  @CONFERENCE{Mohsen Hosseini202267,
  author = {Mohsen Hosseini, Seyed and Carli, Raffaele and Jantzen, Jan and Dotoli, Mariagrazia},
  title = {Multi-block ADMM Approach for Decentralized Demand Response of Energy Communities with Flexible Loads and Shared Energy Storage System},
  year = {2022},
  journal = {2022 30th Mediterranean Conference on Control and Automation, MED 2022},
  pages = {67 – 72},
  doi = {10.1109/MED54222.2022.9837173},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136256232&doi=10.1109%2fMED54222.2022.9837173&partnerID=40&md5=05482ee51ee4bd7730a9109693de5802},
  abstract = {This paper proposes a novel decentralized energy scheduling framework for demand response of energy communities in the case of limited overall capacity of distribution networks. A combined energy scheduling of heating, ventilation, and air conditioning systems and a community energy storage system (CESS) for multiple smart residential users is presented. The proposed approach aims at minimizing the total expected energy costs while ensuring the occupants' thermal comfort. The optimization problem is first formulated as a mixed-integer linear programming problem, which is converted into a linear programming problem using a tractable approximation method based on a non-complementary charging/discharging strategy of the CESS. The decentralized resolution process is based on multi-block proximal Jacobian alternating direction method of multipliers, ensuring efficient computation and protecting users' privacy. We assess the effectiveness of the proposed approach through numerical experiments on a realistic case study. © 2022 IEEE.},
  author_keywords = {alternating direction method of multipliers (ADMM); decentralized control; demand response; energy communities; energy storage},
  keywords = {Air conditioning; Decentralized control; Integer programming; Scheduling; Alternating direction method of multiplier; Alternating directions method of multipliers; Decentralised; Decentralised control; Demand response; Energy; Energy community; Multiblocks; Response of energy; Storage systems; Energy storage},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 12}
  }

• Proia, S., Carli, R., Cavone, G. & Dotoli, M. (2022) Control Techniques for Safe, Ergonomic, and Efficient Human-Robot Collaboration in the Digital Industry: A Survey. IN IEEE Transactions on Automation Science and Engineering, 19.1798 – 1819. doi:10.1109/TASE.2021.3131011
  [BibTeX] [Abstract] [Download PDF]

  The fourth industrial revolution, also known as Industry 4.0, is reshaping the way individuals live and work while providing a substantial influence on the manufacturing scenario. The key enabling technology that has made Industry 4.0 a concrete reality is without doubt collaborative robotics, which is also evolving as a fundamental pillar of the next revolution, the so-called Industry 5.0. The improvement of employees’ safety and well-being, together with the increase of profitability and productivity, are indeed the main goals of human-robot collaboration (HRC) in the industrial setting. The robotic controller design and the analysis of existing decision and control techniques are crucially needed to develop innovative models and state-of-the-art methodologies for a safe, ergonomic, and efficient HRC. To this aim, this paper presents an accurate review of the most recent and relevant contributions to the related literature, focusing on the control perspective. All the surveyed works are carefully selected and categorized by target (i.e., safety, ergonomics, and efficiency), and then by problem and type of control, in presence or absence of optimization. Finally, the discussion of the achieved results and the analysis of the emerging challenges in this research field are reported, highlighting the identified gaps and the promising future developments in the context of the digital evolution. © 2004-2012 IEEE.

  @ARTICLE{Proia20221798,
  author = {Proia, Silvia and Carli, Raffaele and Cavone, Graziana and Dotoli, Mariagrazia},
  title = {Control Techniques for Safe, Ergonomic, and Efficient Human-Robot Collaboration in the Digital Industry: A Survey},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {3},
  pages = {1798 – 1819},
  doi = {10.1109/TASE.2021.3131011},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121365732&doi=10.1109%2fTASE.2021.3131011&partnerID=40&md5=eae23f3b0dbfaf83b934942c9c0736ff},
  abstract = {The fourth industrial revolution, also known as Industry 4.0, is reshaping the way individuals live and work while providing a substantial influence on the manufacturing scenario. The key enabling technology that has made Industry 4.0 a concrete reality is without doubt collaborative robotics, which is also evolving as a fundamental pillar of the next revolution, the so-called Industry 5.0. The improvement of employees' safety and well-being, together with the increase of profitability and productivity, are indeed the main goals of human-robot collaboration (HRC) in the industrial setting. The robotic controller design and the analysis of existing decision and control techniques are crucially needed to develop innovative models and state-of-the-art methodologies for a safe, ergonomic, and efficient HRC. To this aim, this paper presents an accurate review of the most recent and relevant contributions to the related literature, focusing on the control perspective. All the surveyed works are carefully selected and categorized by target (i.e., safety, ergonomics, and efficiency), and then by problem and type of control, in presence or absence of optimization. Finally, the discussion of the achieved results and the analysis of the emerging challenges in this research field are reported, highlighting the identified gaps and the promising future developments in the context of the digital evolution. © 2004-2012 IEEE.},
  author_keywords = {cobots; collaborative robotics; efficiency; ergonomics; HRC control systems; human-robot collaboration (HRC); industrial automation; Industry 4.0; safety},
  keywords = {Collaborative robots; Controllers; Efficiency; Ergonomics; Industry 4.0; Job analysis; Robotics; Surveys; Collaboration; Control techniques; Efficiency.; Human-robot collaboration; Human-robot collaboration control system; Industrial automation; Service robots; Task analysis; Accident prevention},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 68; All Open Access, Hybrid Gold Open Access}
  }

• Dammacco, L., Carli, R., Lazazzera, V., Fiorentino, M. & Dotoli, M. (2022) Simulation-based Design for the Layout and Operation of AGVs in Sustainable and Efficient Manufacturing Systems IN Proceedings of the International Conference on Cyber-Physical Social Intelligence, ICCSI 2022., 309 – 314. doi:10.1109/ICCSI55536.2022.9970620
  [BibTeX] [Abstract] [Download PDF]

  Complex manufacturing systems are recently undergoing a green revolution due to manufacturing customization towards sustainable products. A key enabler for the implementation of green and energy efficient production is simulation-based design, which supports system engineers and designers in making decision choices aimed at enhancing the performance of smart and sustainable production. In this context, this work proposes a simulation approach to support the design of the layout and operation of automated guided vehicles (AGVs) in complex production lines. In particular, a case study related to the assembly of electric axles for heavy-duty vehicles is presented: a scenario analysis implemented in the Plant Simulation platform is used to determine the optimal configuration of AGVs in terms of number of vehicles and operation (e.g., definition of charging strategies, scheduling of charging stops, routing). The simulation results first show that the reduction of the AGVs’ energy consumption and the increase of production throughput are competing criteria; second, the choice of AGV charging strategies has a significant influence on the energy consumption as well as on the productivity performance. © 2022 IEEE.

  @CONFERENCE{Dammacco2022309,
  author = {Dammacco, Lucilla and Carli, Raffaele and Lazazzera, Vito and Fiorentino, Michele and Dotoli, Mariagrazia},
  title = {Simulation-based Design for the Layout and Operation of AGVs in Sustainable and Efficient Manufacturing Systems},
  year = {2022},
  journal = {Proceedings of the International Conference on Cyber-Physical Social Intelligence, ICCSI 2022},
  pages = {309 – 314},
  doi = {10.1109/ICCSI55536.2022.9970620},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145662907&doi=10.1109%2fICCSI55536.2022.9970620&partnerID=40&md5=29f65c54294fd15458b294507bca7628},
  abstract = {Complex manufacturing systems are recently undergoing a green revolution due to manufacturing customization towards sustainable products. A key enabler for the implementation of green and energy efficient production is simulation-based design, which supports system engineers and designers in making decision choices aimed at enhancing the performance of smart and sustainable production. In this context, this work proposes a simulation approach to support the design of the layout and operation of automated guided vehicles (AGVs) in complex production lines. In particular, a case study related to the assembly of electric axles for heavy-duty vehicles is presented: a scenario analysis implemented in the Plant Simulation platform is used to determine the optimal configuration of AGVs in terms of number of vehicles and operation (e.g., definition of charging strategies, scheduling of charging stops, routing). The simulation results first show that the reduction of the AGVs' energy consumption and the increase of production throughput are competing criteria; second, the choice of AGV charging strategies has a significant influence on the energy consumption as well as on the productivity performance. © 2022 IEEE.},
  author_keywords = {automated guided vehicle (AGV); Complex manufacturing systems; discrete event simulation; sustainable and efficient manufacturing; what-if analysis},
  keywords = {Automatic guided vehicles; Energy efficiency; Energy utilization; Simulation platform; Throughput; Automated guided vehicle; Automated guided vehicles; Charging strategies; Complex manufacturing systems; Customisation; Discrete-event simulations; Green revolution; Simulation-based designs; Sustainable and efficient manufacturing; What-if Analysis; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Helmi, A. M., Carli, R., Dotoli, M. & Ramadan, H. S. (2022) Efficient and Sustainable Reconfiguration of Distribution Networks via Metaheuristic Optimization. IN IEEE Transactions on Automation Science and Engineering, 19.82 – 98. doi:10.1109/TASE.2021.3072862
  [BibTeX] [Abstract] [Download PDF]

  Improving the efficiency and sustainability of distribution networks (DNs) is nowadays a challenging objective both for large networks and microgrids connected to the main grid. In this context, a crucial role is played by the so-called network reconfiguration problem, which aims at determining the optimal DN topology. This process is enabled by properly changing the close/open status of all available branch switches to form an admissible graph connecting network buses. The reconfiguration problem is typically modeled as an NP-hard combinatorial problem with a complex search space due to current and voltage constraints. Even though several metaheuristic algorithms have been used to obtain – without guarantees – the global optimal solution, searching for near-optimal solutions in reasonable time is still a research challenge for the DN reconfiguration problem. Facing this issue, this article proposes a novel effective optimization framework for the reconfiguration problem of modern DNs. The objective of reconfiguration is minimizing the overall power losses while ensuring an enhanced DN voltage profile. A multiple-step resolution procedure is then presented, where the recent Harris hawks optimization (HHO) algorithm constitutes the core part. This optimizer is here intelligently accompanied by appropriate preprocessing (i.e., search space preparation and initial feasible population generation) and postprocessing (i.e., solution refinement) phases aimed at improving the search for near-optimal configurations. The effectiveness of the method is validated through numerical experiments on the IEEE 33-bus, the IEEE 85-bus systems, and an artificial 295-bus system under distributed generation and load variation. Finally, the performance of the proposed HHO-based approach is compared with two related metaheuristic techniques, namely the particle swarm optimization algorithm and the Cuckoo search algorithm. The results show that HHO outperforms the other two optimizers in terms of minimized power losses, enhanced voltage profile, and running time. Note to Practitioners – This article is motivated by the emerging need for effective network reconfiguration approaches in modern power distribution systems, including microgrids. The proposed metaheuristic optimization strategy allows the decision maker (i.e., the distribution system operator) to determine in reasonable time the optimal network topology, minimizing the overall power losses and considering the system operational requirements. The proposed optimization framework is generic and flexible, as it can be applied to different architectures both of large distribution networks (DNs) and microgrids, considering various types of system objectives and technical constraints. The presented strategy can be implemented in any decision support system or engineering software for power grids, providing decision makers with an effective information and communication technology tool for the optimal planning of the energy efficiency and environmental sustainability of DNs. © 2004-2012 IEEE.

  @ARTICLE{Helmi202282,
  author = {Helmi, Ahmed M. and Carli, Raffaele and Dotoli, Mariagrazia and Ramadan, Haitham S.},
  title = {Efficient and Sustainable Reconfiguration of Distribution Networks via Metaheuristic Optimization},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {1},
  pages = {82 – 98},
  doi = {10.1109/TASE.2021.3072862},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105879516&doi=10.1109%2fTASE.2021.3072862&partnerID=40&md5=1b9b5290b92a3a5ad8886f61ec903dc8},
  abstract = {Improving the efficiency and sustainability of distribution networks (DNs) is nowadays a challenging objective both for large networks and microgrids connected to the main grid. In this context, a crucial role is played by the so-called network reconfiguration problem, which aims at determining the optimal DN topology. This process is enabled by properly changing the close/open status of all available branch switches to form an admissible graph connecting network buses. The reconfiguration problem is typically modeled as an NP-hard combinatorial problem with a complex search space due to current and voltage constraints. Even though several metaheuristic algorithms have been used to obtain - without guarantees - the global optimal solution, searching for near-optimal solutions in reasonable time is still a research challenge for the DN reconfiguration problem. Facing this issue, this article proposes a novel effective optimization framework for the reconfiguration problem of modern DNs. The objective of reconfiguration is minimizing the overall power losses while ensuring an enhanced DN voltage profile. A multiple-step resolution procedure is then presented, where the recent Harris hawks optimization (HHO) algorithm constitutes the core part. This optimizer is here intelligently accompanied by appropriate preprocessing (i.e., search space preparation and initial feasible population generation) and postprocessing (i.e., solution refinement) phases aimed at improving the search for near-optimal configurations. The effectiveness of the method is validated through numerical experiments on the IEEE 33-bus, the IEEE 85-bus systems, and an artificial 295-bus system under distributed generation and load variation. Finally, the performance of the proposed HHO-based approach is compared with two related metaheuristic techniques, namely the particle swarm optimization algorithm and the Cuckoo search algorithm. The results show that HHO outperforms the other two optimizers in terms of minimized power losses, enhanced voltage profile, and running time. Note to Practitioners - This article is motivated by the emerging need for effective network reconfiguration approaches in modern power distribution systems, including microgrids. The proposed metaheuristic optimization strategy allows the decision maker (i.e., the distribution system operator) to determine in reasonable time the optimal network topology, minimizing the overall power losses and considering the system operational requirements. The proposed optimization framework is generic and flexible, as it can be applied to different architectures both of large distribution networks (DNs) and microgrids, considering various types of system objectives and technical constraints. The presented strategy can be implemented in any decision support system or engineering software for power grids, providing decision makers with an effective information and communication technology tool for the optimal planning of the energy efficiency and environmental sustainability of DNs. © 2004-2012 IEEE.},
  author_keywords = {Distribution network (DN) reconfiguration; Harris hawks optimization (HHO) algorithm; metaheuristic optimization; microgrids; power losses reduction; voltage profile improvement},
  keywords = {Microgrids; NP-hard; Numerical methods; Optimal systems; Particle swarm optimization (PSO); Cuckoo search algorithms; Global optimal solutions; Meta heuristic algorithm; Meta-heuristic optimizations; Meta-heuristic techniques; Network re-configuration; Particle swarm optimization algorithm; Reconfiguration of distribution networks; Internet protocols},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 88}
  }

• Dammacco, L., Carli, R., Lazazzera, V., Fiorentino, M. & Dotoli, M. (2022) Designing complex manufacturing systems by virtual reality: A novel approach and its application to the virtual commissioning of a production line. IN Computers in Industry, 143.. doi:10.1016/j.compind.2022.103761
  [BibTeX] [Abstract] [Download PDF]

  The design of complex manufacturing systems (CMSs) is challenging, because of the requirements of efficiency, safety, and ergonomics, and the need of optimizing resources, i.e., space, machines, operators, and data. Virtual reality (VR) – one of the promising technologies at the base of Industry 4.0 – is able to address the design issues of CMSs, and even decrease costs and time when employed from the initial conception to the final validation of production lines, since it facilitates their virtual commissioning, i.e., it enables the full verification of systems and related components by virtual inspection and tests. Despite the above advantages, VR is still rarely used in the design of CMSs, and there is no standard VR approach in industry yet. In addition, the related scientific literature is scarce and often limited to small or simplified cases. To fill this gap, this work presents a novel VR-based approach for designing CMSs, composed of four phases: Three-dimensional CAD Export, Model Import, Scene Creation, and VR Review. The proposed approach is applied to a real industrial use case related to the virtual commissioning of an electric axles production line and it is evaluated through a questionnaire from industry professionals. The case study shows that using the VR technology enhanced the technical communication between experts in the teamwork, and it was particularly effective in finding ergonomics flaws like issues in visibility, reach, and posture using a virtual golden zone. In addition, all users found the VR interaction enjoyable and easy to learn, and beginner users perceived a comparable workload as advanced users. © 2022 Elsevier B.V.

  @ARTICLE{Dammacco2022,
  author = {Dammacco, Lucilla and Carli, Raffaele and Lazazzera, Vito and Fiorentino, Michele and Dotoli, Mariagrazia},
  title = {Designing complex manufacturing systems by virtual reality: A novel approach and its application to the virtual commissioning of a production line},
  year = {2022},
  journal = {Computers in Industry},
  volume = {143},
  doi = {10.1016/j.compind.2022.103761},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136109989&doi=10.1016%2fj.compind.2022.103761&partnerID=40&md5=c803a45d690d457ee75499235ee266ec},
  abstract = {The design of complex manufacturing systems (CMSs) is challenging, because of the requirements of efficiency, safety, and ergonomics, and the need of optimizing resources, i.e., space, machines, operators, and data. Virtual reality (VR) – one of the promising technologies at the base of Industry 4.0 – is able to address the design issues of CMSs, and even decrease costs and time when employed from the initial conception to the final validation of production lines, since it facilitates their virtual commissioning, i.e., it enables the full verification of systems and related components by virtual inspection and tests. Despite the above advantages, VR is still rarely used in the design of CMSs, and there is no standard VR approach in industry yet. In addition, the related scientific literature is scarce and often limited to small or simplified cases. To fill this gap, this work presents a novel VR-based approach for designing CMSs, composed of four phases: Three-dimensional CAD Export, Model Import, Scene Creation, and VR Review. The proposed approach is applied to a real industrial use case related to the virtual commissioning of an electric axles production line and it is evaluated through a questionnaire from industry professionals. The case study shows that using the VR technology enhanced the technical communication between experts in the teamwork, and it was particularly effective in finding ergonomics flaws like issues in visibility, reach, and posture using a virtual golden zone. In addition, all users found the VR interaction enjoyable and easy to learn, and beginner users perceived a comparable workload as advanced users. © 2022 Elsevier B.V.},
  author_keywords = {Complex manufacturing systems; Human computer interaction; Industry 4.0; System design; Virtual commissioning; Virtual reality},
  keywords = {Computer aided design; Electric lines; Human computer interaction; Industry 4.0; Virtual addresses; Complex manufacturing systems; Design issues; Designing complex; ITS applications; Machine data; Machine operators; Production line; Virtual commissioning; Virtual inspection; Virtual tests; Virtual reality},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 21}
  }

• Scarabaggio, P., Carli, R., Cavone, G., Epicoco, N. & Dotoli, M. (2022) Nonpharmaceutical Stochastic Optimal Control Strategies to Mitigate the COVID-19 Spread. IN IEEE Transactions on Automation Science and Engineering, 19.560 – 575. doi:10.1109/TASE.2021.3111338
  [BibTeX] [Abstract] [Download PDF]

  This article proposes a stochastic nonlinear model predictive controller to support policymakers in determining robust optimal nonpharmaceutical strategies to tackle the COVID-19 pandemic waves. First, a time-varying SIRCQTHE epidemiological model is defined to get predictions on the pandemic dynamics. A stochastic model predictive control problem is then formulated to select the necessary control actions (i.e., restrictions on the mobility for different socioeconomic categories) to minimize the socioeconomic costs. In particular, considering the uncertainty characterizing this decision-making process, we ensure that the capacity of the healthcare system is not violated in accordance with a chance constraint approach. The effectiveness of the presented method in properly supporting the definition of diversified nonpharmaceutical strategies for tackling the COVID-19 spread is tested on the network of Italian regions using real data. The proposed approach can be easily extended to cope with other countries’ characteristics and different levels of the spatial scale. Note to Practitioners – This article is motivated by the emerging need for developing effective methods to support policymakers in mitigating the effects of the COVID-19 pandemic. The proposed feedback control strategy – combining a multiregion epidemiological model with a nonlinear stochastic model predictive control approach – allows the robust identification of the most effective restrictive measures considering the corresponding effects on the healthcare and socioeconomic systems. The proposed framework is a general and flexible method that can be applied to various real scenarios, leveraging mobility data, available from the Google mobility service, to recognize patterns and predict future behaviors of individuals. © 2004-2012 IEEE.

  @ARTICLE{Scarabaggio2022560,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Cavone, Graziana and Epicoco, Nicola and Dotoli, Mariagrazia},
  title = {Nonpharmaceutical Stochastic Optimal Control Strategies to Mitigate the COVID-19 Spread},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {2},
  pages = {560 – 575},
  doi = {10.1109/TASE.2021.3111338},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115686920&doi=10.1109%2fTASE.2021.3111338&partnerID=40&md5=ef02a3b0f8f2eeff0ec2f0e0a861a0b8},
  abstract = {This article proposes a stochastic nonlinear model predictive controller to support policymakers in determining robust optimal nonpharmaceutical strategies to tackle the COVID-19 pandemic waves. First, a time-varying SIRCQTHE epidemiological model is defined to get predictions on the pandemic dynamics. A stochastic model predictive control problem is then formulated to select the necessary control actions (i.e., restrictions on the mobility for different socioeconomic categories) to minimize the socioeconomic costs. In particular, considering the uncertainty characterizing this decision-making process, we ensure that the capacity of the healthcare system is not violated in accordance with a chance constraint approach. The effectiveness of the presented method in properly supporting the definition of diversified nonpharmaceutical strategies for tackling the COVID-19 spread is tested on the network of Italian regions using real data. The proposed approach can be easily extended to cope with other countries' characteristics and different levels of the spatial scale. Note to Practitioners - This article is motivated by the emerging need for developing effective methods to support policymakers in mitigating the effects of the COVID-19 pandemic. The proposed feedback control strategy - combining a multiregion epidemiological model with a nonlinear stochastic model predictive control approach - allows the robust identification of the most effective restrictive measures considering the corresponding effects on the healthcare and socioeconomic systems. The proposed framework is a general and flexible method that can be applied to various real scenarios, leveraging mobility data, available from the Google mobility service, to recognize patterns and predict future behaviors of individuals. © 2004-2012 IEEE.},
  author_keywords = {COVID-19; epidemic control; mitigation strategies; pandemic modeling; stochastic model predictive control (MPC)},
  keywords = {Decision making; Disease control; Model predictive control; Optimization; Predictive control systems; Random processes; Stochastic control systems; Stochastic models; COVID-19; Epidemic control; Medical services; Mitigation strategy; Pandemic; Pandemic modeling; Predictive models; Stochastic model predictive control .; Stochastic model predictive controls; Uncertainty; Stochastic systems},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 22; All Open Access, Green Open Access}
  }

• Cavone, G., Van Den Boom, T., Blenkers, L., Dotoli, M., Seatzu, C. & De Schutter, B. (2022) An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks. IN IEEE Transactions on Automation Science and Engineering, 19.99 – 112. doi:10.1109/TASE.2020.3040940
  [BibTeX] [Abstract] [Download PDF]

  Railways are a well-recognized sustainable transportation mode that helps to satisfy the continuously growing mobility demand. However, the management of railway traffic in large-scale networks is a challenging task, especially when both a major disruption and various disturbances occur simultaneously. We propose an automatic rescheduling algorithm for real-time control of railway traffic that aims at minimizing the delays induced by the disruption and disturbances, as well as the resulting cancellations of train runs and turn-backs (or short-turns) and shuntings of trains in stations. The real-time control is based on the Model Predictive Control (MPC) scheme where the rescheduling problem is solved by mixed integer linear programming using macroscopic and mesoscopic models. The proposed resolution algorithm combines a distributed optimization method and bi-level heuristics to provide feasible control actions for the whole network in short computation time, without neglecting physical limitations nor operations at disrupted stations. A realistic simulation test is performed on the complete Dutch railway network. The results highlight the effectiveness of the method in properly minimizing the delays and rapidly providing feasible feedback control actions for the whole network. Note to Practitioners – This article aims at contributing to the enhancement of the core functionalities of Automatic Train Control (ATC) systems and, in particular, of the Automatic Train Supervision (ATS) module, which is included in ATC systems. In general, the ATS module allows to automate the train traffic supervision and consequently the rescheduling of the railway traffic in case of unexpected events. However, the implementation of an efficient rescheduling technique that automatically and rapidly provides the control actions necessary to restore the railway traffic operations to the nominal schedule is still an open issue. Most literature contributions fail in providing rescheduling methods that successfully determine high-quality solutions in less than one minute and include real-time information regarding the large-scale railway system state. This research proposes a semi-heuristic control algorithm based on MPC that, on the one hand, overcomes the limitations of manual rescheduling (i.e., suboptimal, stressful, and delayed decisions) and, on the other hand, offers the advantages of online and closed-loop control of railway traffic based on continuous monitoring of the traffic state to rapidly restore railway traffic operations to the nominal schedule. The semi-heuristic procedure permits to significantly reduce the computation time necessary to solve the rescheduling problem compared with an exact procedure; moreover, the use of a distributed optimization approach permits the application of the algorithm to large instances of the rescheduling problem, and the inclusion of both the traffic and rolling stock constraints related to the disrupted area. The method is tested on a realistic simulation environment, thus still requires further refinements for the integration into a real ATS system. Further developments will also consider the occurrence of various simultaneous disruptions in the network. © 2004-2012 IEEE.

  @ARTICLE{Cavone202299,
  author = {Cavone, Graziana and Van Den Boom, Ton and Blenkers, Lex and Dotoli, Mariagrazia and Seatzu, Carla and De Schutter, Bart},
  title = {An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {1},
  pages = {99 – 112},
  doi = {10.1109/TASE.2020.3040940},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098771253&doi=10.1109%2fTASE.2020.3040940&partnerID=40&md5=155dc1581a4c1e8c1c487e2eb7c75cbd},
  abstract = {Railways are a well-recognized sustainable transportation mode that helps to satisfy the continuously growing mobility demand. However, the management of railway traffic in large-scale networks is a challenging task, especially when both a major disruption and various disturbances occur simultaneously. We propose an automatic rescheduling algorithm for real-time control of railway traffic that aims at minimizing the delays induced by the disruption and disturbances, as well as the resulting cancellations of train runs and turn-backs (or short-turns) and shuntings of trains in stations. The real-time control is based on the Model Predictive Control (MPC) scheme where the rescheduling problem is solved by mixed integer linear programming using macroscopic and mesoscopic models. The proposed resolution algorithm combines a distributed optimization method and bi-level heuristics to provide feasible control actions for the whole network in short computation time, without neglecting physical limitations nor operations at disrupted stations. A realistic simulation test is performed on the complete Dutch railway network. The results highlight the effectiveness of the method in properly minimizing the delays and rapidly providing feasible feedback control actions for the whole network. Note to Practitioners - This article aims at contributing to the enhancement of the core functionalities of Automatic Train Control (ATC) systems and, in particular, of the Automatic Train Supervision (ATS) module, which is included in ATC systems. In general, the ATS module allows to automate the train traffic supervision and consequently the rescheduling of the railway traffic in case of unexpected events. However, the implementation of an efficient rescheduling technique that automatically and rapidly provides the control actions necessary to restore the railway traffic operations to the nominal schedule is still an open issue. Most literature contributions fail in providing rescheduling methods that successfully determine high-quality solutions in less than one minute and include real-time information regarding the large-scale railway system state. This research proposes a semi-heuristic control algorithm based on MPC that, on the one hand, overcomes the limitations of manual rescheduling (i.e., suboptimal, stressful, and delayed decisions) and, on the other hand, offers the advantages of online and closed-loop control of railway traffic based on continuous monitoring of the traffic state to rapidly restore railway traffic operations to the nominal schedule. The semi-heuristic procedure permits to significantly reduce the computation time necessary to solve the rescheduling problem compared with an exact procedure; moreover, the use of a distributed optimization approach permits the application of the algorithm to large instances of the rescheduling problem, and the inclusion of both the traffic and rolling stock constraints related to the disrupted area. The method is tested on a realistic simulation environment, thus still requires further refinements for the integration into a real ATS system. Further developments will also consider the occurrence of various simultaneous disruptions in the network. © 2004-2012 IEEE.},
  author_keywords = {Mixed Integer Linear (MIL) Programming (MILP); Model Predictive Control (MPC); railway traffic disruption; rescheduling algorithms},
  keywords = {Heuristic methods; Integer programming; Model predictive control; Predictive control systems; Railroads; Real time control; Distributed optimization; Large-scale network; Mixed integer linear programming; Physical limitations; Realistic simulation; Rescheduling problem; Resolution algorithms; Sustainable transportation; Automatic train control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 33; All Open Access, Green Open Access}
  }

• Bozza, A., Askari, B., Cavone, G., Carli, R. & Dotoli, M. (2022) An Adaptive Model Predictive Control Approach for Position Tracking and Force Control of a Hydraulic Actuator IN IEEE International Conference on Automation Science and Engineering., 1029 – 1034. doi:10.1109/CASE49997.2022.9926645
  [BibTeX] [Abstract] [Download PDF]

  This paper presents an Adaptive Model Predictive Control (AMPC) approach for the position tracking and force control of a hydraulic actuator (HA). Due to its nonlinear dynamics, the iterative linearization paradigm is employed to approximate the HA system by a linear time-varying model. Such a representation is used as the internal plant model of the predictive controller to effectively make predictions on the system state. The effectiveness of the proposed AMPC architecture is shown through numerical experiments addressing the control of a real HA on different scenarios. Finally, a comparative analysis on several values of sampling time, prediction and control horizon is carried out in order to investigate the effect of the parameters tuning on the performance of the closed-loop control system. © 2022 IEEE.

  @CONFERENCE{Bozza20221029,
  author = {Bozza, Augusto and Askari, Bahman and Cavone, Graziana and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {An Adaptive Model Predictive Control Approach for Position Tracking and Force Control of a Hydraulic Actuator},
  year = {2022},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2022-August},
  pages = {1029 – 1034},
  doi = {10.1109/CASE49997.2022.9926645},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141675790&doi=10.1109%2fCASE49997.2022.9926645&partnerID=40&md5=8ea9bb1c05f9c04a733472aeef5755d1},
  abstract = {This paper presents an Adaptive Model Predictive Control (AMPC) approach for the position tracking and force control of a hydraulic actuator (HA). Due to its nonlinear dynamics, the iterative linearization paradigm is employed to approximate the HA system by a linear time-varying model. Such a representation is used as the internal plant model of the predictive controller to effectively make predictions on the system state. The effectiveness of the proposed AMPC architecture is shown through numerical experiments addressing the control of a real HA on different scenarios. Finally, a comparative analysis on several values of sampling time, prediction and control horizon is carried out in order to investigate the effect of the parameters tuning on the performance of the closed-loop control system. © 2022 IEEE.},
  author_keywords = {Adaptive MPC; Hydraulic Actuator; Model Linearization; Nonlinear Systems; Position and Force Tracking},
  keywords = {Adaptive control systems; Closed loop control systems; Hydraulic actuators; Linearization; Predictive control systems; Actuator system; Adaptive model predictive control; Adaptive MPC; Force tracking; Iterative linearizations; Model linearization; Model-predictive control approach; Position and force tracking; Position tracking control; Position/force control; Model predictive control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Scarabaggio, P., Grammatico, S., Carli, R. & Dotoli, M. (2022) Distributed Demand Side Management with Stochastic Wind Power Forecasting. IN IEEE Transactions on Control Systems Technology, 30.97 – 112. doi:10.1109/TCST.2021.3056751
  [BibTeX] [Abstract] [Download PDF]

  In this article, we propose a distributed demand-side management (DSM) approach for smart grids taking into account uncertainty in wind power forecasting. The smart grid model comprehends traditional users as well as active users (prosumers). Through a rolling-horizon approach, prosumers participate in a DSM program, aiming at minimizing their cost in the presence of uncertain wind power generation by a game theory approach. We assume that each user selfishly formulates its grid optimization problem as a noncooperative game. The core challenge in this article is defining an approach to cope with the uncertainty in wind power availability. We tackle this issue from two different sides: by employing the expected value to define a deterministic counterpart for the problem and by adopting a stochastic approximated framework. In the latter case, we employ the sample average approximation (SAA) technique, whose results are based on a probability density function (PDF) for the wind speed forecasts. We improve the PDF by using historical wind speed data, and by employing a control index that takes into account the weather condition stability. Numerical simulations on a real data set show that the proposed stochastic strategy generates lower individual costs compared to the standard expected value approach. © 1993-2012 IEEE.

  @ARTICLE{Scarabaggio202297,
  author = {Scarabaggio, Paolo and Grammatico, Sergio and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Distributed Demand Side Management with Stochastic Wind Power Forecasting},
  year = {2022},
  journal = {IEEE Transactions on Control Systems Technology},
  volume = {30},
  number = {1},
  pages = {97 – 112},
  doi = {10.1109/TCST.2021.3056751},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100918524&doi=10.1109%2fTCST.2021.3056751&partnerID=40&md5=4f491e205e325ad467291e71ce8dbff8},
  abstract = {In this article, we propose a distributed demand-side management (DSM) approach for smart grids taking into account uncertainty in wind power forecasting. The smart grid model comprehends traditional users as well as active users (prosumers). Through a rolling-horizon approach, prosumers participate in a DSM program, aiming at minimizing their cost in the presence of uncertain wind power generation by a game theory approach. We assume that each user selfishly formulates its grid optimization problem as a noncooperative game. The core challenge in this article is defining an approach to cope with the uncertainty in wind power availability. We tackle this issue from two different sides: by employing the expected value to define a deterministic counterpart for the problem and by adopting a stochastic approximated framework. In the latter case, we employ the sample average approximation (SAA) technique, whose results are based on a probability density function (PDF) for the wind speed forecasts. We improve the PDF by using historical wind speed data, and by employing a control index that takes into account the weather condition stability. Numerical simulations on a real data set show that the proposed stochastic strategy generates lower individual costs compared to the standard expected value approach. © 1993-2012 IEEE.},
  author_keywords = {Demand-side management (DSM); model predictive control; sample average approximation (SAA); smart grid; stochastic optimization},
  keywords = {Electric power generation; Electric power transmission networks; Electric utilities; Game theory; Probability density function; Smart power grids; Stochastic systems; Weather forecasting; Wind; Wind power; Grid optimization; Noncooperative game; Probability density function (pdf); Sample average approximation; Stochastic winds; Wind power availability; Wind power forecasting; Wind speed forecast; Demand side management},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 88; All Open Access, Green Open Access}
  }

• Proia, S., Cavone, G., Camposeo, A., Ceglie, F., Carli, R. & Dotoli, M. (2022) Safe and Ergonomic Human-Drone Interaction in Warehouses IN IEEE International Conference on Intelligent Robots and Systems., 6681 – 6686. doi:10.1109/IROS47612.2022.9981469
  [BibTeX] [Abstract] [Download PDF]

  This paper presents an application of human-drone interaction (HDI) for inventory management in a ware-house 4.0 that aims at improving the operators’ safety and well-being together with increasing efficiency and reducing production costs. In our work, the speed and separation monitoring (SSM) methodology is applied for the first time to HDI, in analogy to the human-robot interaction (HRI) ISO safety requirements as well as the rapid upper limb assessment (RULA), for evaluating the operator’s ergonomic posture during the interaction with the drone. With the aim of validating the proposed approach in a realistic scenario, a quadrotor is controlled to perform a pick and place task along a desired trajectory, from the picking bay to the palletizing area where the operator is located, avoiding collisions with the warehouse shelves by implementing the artificial potential field technique (APF) for planning and the linear quadratic regulator (LQR) and iterative LQR (iLQR) algorithms for tracking. The obtained results of the HDI architecture simulations are presented and discussed in detail proving the effectiveness of the proposed method for a safe and ergonomic HDI. © 2022 IEEE.

  @CONFERENCE{Proia20226681,
  author = {Proia, Silvia and Cavone, Graziana and Camposeo, Antonio and Ceglie, Fabio and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Safe and Ergonomic Human-Drone Interaction in Warehouses},
  year = {2022},
  journal = {IEEE International Conference on Intelligent Robots and Systems},
  volume = {2022-October},
  pages = {6681 – 6686},
  doi = {10.1109/IROS47612.2022.9981469},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146319710&doi=10.1109%2fIROS47612.2022.9981469&partnerID=40&md5=61b20f9f8ff557ea77ff2ae551b6207b},
  abstract = {This paper presents an application of human-drone interaction (HDI) for inventory management in a ware-house 4.0 that aims at improving the operators' safety and well-being together with increasing efficiency and reducing production costs. In our work, the speed and separation monitoring (SSM) methodology is applied for the first time to HDI, in analogy to the human-robot interaction (HRI) ISO safety requirements as well as the rapid upper limb assessment (RULA), for evaluating the operator's ergonomic posture during the interaction with the drone. With the aim of validating the proposed approach in a realistic scenario, a quadrotor is controlled to perform a pick and place task along a desired trajectory, from the picking bay to the palletizing area where the operator is located, avoiding collisions with the warehouse shelves by implementing the artificial potential field technique (APF) for planning and the linear quadratic regulator (LQR) and iterative LQR (iLQR) algorithms for tracking. The obtained results of the HDI architecture simulations are presented and discussed in detail proving the effectiveness of the proposed method for a safe and ergonomic HDI. © 2022 IEEE.},
  author_keywords = {aerial robotics; ergonomics; Human-drone interaction; quadrotor; safety; speed and separation monitoring; trajectory planning; trajectory tracking},
  keywords = {Antennas; Ergonomics; Human robot interaction; Inventory control; Iterative methods; Robot programming; Trajectories; Warehouses; Aerial robotics; Human-drone interaction; Inventory management; Operator safety; Production cost; Quad rotors; Speed and separation monitoring; Trajectory Planning; Trajectory-tracking; Well being; Drones},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 5}
  }

• Askari, B., Carli, R., Cavone, G. & Dotoli, M. (2022) Data-Driven Fault Diagnosis in a Complex Hydraulic System based on Early Classification IN IFAC-PapersOnLine., 187 – 192. doi:10.1016/j.ifacol.2023.01.070
  [BibTeX] [Abstract] [Download PDF]

  In this paper, an early time-series classification (ETSC) algorithm is applied to support fault diagnosis in a complex hydraulic system (HS) with several interconnected components. The proposed technique aims at early classifying the state of the system while keeping the loss of classification inaccuracy at the minimum level. In contrast to baseline models that detect the eventual faults at the end of each working cycle, the ETSC model can diagnose any fault type of the HS components before observing the entire working cycle. Indeed, the early classification model successfully achieves a trade-off between the accuracy and the earliness criterion. Experimental results on a realistic HS dataset from the related literature show that the ETSC method can effectively identify different fault types with a higher accuracy and earlier compared to baseline methodologies. Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

  @CONFERENCE{Askari2022187,
  author = {Askari, Bahman and Carli, Raffaele and Cavone, Graziana and Dotoli, Mariagrazia},
  title = {Data-Driven Fault Diagnosis in a Complex Hydraulic System based on Early Classification},
  year = {2022},
  journal = {IFAC-PapersOnLine},
  volume = {55},
  number = {40},
  pages = {187 – 192},
  doi = {10.1016/j.ifacol.2023.01.070},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159280640&doi=10.1016%2fj.ifacol.2023.01.070&partnerID=40&md5=ab3c6dd293b6af56ac23ff81957cc262},
  abstract = {In this paper, an early time-series classification (ETSC) algorithm is applied to support fault diagnosis in a complex hydraulic system (HS) with several interconnected components. The proposed technique aims at early classifying the state of the system while keeping the loss of classification inaccuracy at the minimum level. In contrast to baseline models that detect the eventual faults at the end of each working cycle, the ETSC model can diagnose any fault type of the HS components before observing the entire working cycle. Indeed, the early classification model successfully achieves a trade-off between the accuracy and the earliness criterion. Experimental results on a realistic HS dataset from the related literature show that the ETSC method can effectively identify different fault types with a higher accuracy and earlier compared to baseline methodologies. Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)},
  author_keywords = {Condition Based Monitoring; Early Classification; Fault Diagnosis; Hydraulic Systems; Machine Learning; Prognostics and Health Management; Time-series},
  keywords = {Computer aided diagnosis; Economic and social effects; Failure analysis; Fault detection; Hydraulic equipment; Information management; Machine learning; Complex hydraulic system; Condition-based monitoring; Early classification; Faults diagnosis; Hydraulic system; Machine-learning; Prognostic and health management; Time series classifications; Times series; Working cycle; Time series},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3; All Open Access, Gold Open Access}
  }

• Robba, M., Dotoli, M. & Paolucci, M. (2022) Guest Editorial Special Section on Advances in Automation and Optimization for Sustainable Transportation and Energy Systems. IN IEEE Transactions on Automation Science and Engineering, 19.3 – 6. doi:10.1109/TASE.2021.3120225
  [BibTeX] [Abstract] [Download PDF]

  This special section of the IEEE Transactions on Automation Science and Engineering (T-ASE) focuses on new models, methods, and technologies for energy efficiency and sustainability in transportation and energy systems. In this section, the focus is thus on articles considering sustainable transportation, such as electric vehicles (EVs), integrated with the smart grid requirements. As guest editors, we are very pleased to present the selected 12 papers, whose topics are specifically related to optimal planning of charging stations (CSs), sustainable transportation and mobility, EVs integration in smart grids, reliability, reduction of consumption, demand response and smart grid modeling, optimal scheduling, routing and charging of fleets of EVs, as well as smart parking. © 2004-2012 IEEE.

  @ARTICLE{Robba20223,
  author = {Robba, Michela and Dotoli, Mariagrazia and Paolucci, Massimo},
  title = {Guest Editorial Special Section on Advances in Automation and Optimization for Sustainable Transportation and Energy Systems},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {1},
  pages = {3 – 6},
  doi = {10.1109/TASE.2021.3120225},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122512182&doi=10.1109%2fTASE.2021.3120225&partnerID=40&md5=f2b16d353939cd47b35e9c38d965c1ca},
  abstract = {This special section of the IEEE Transactions on Automation Science and Engineering (T-ASE) focuses on new models, methods, and technologies for energy efficiency and sustainability in transportation and energy systems. In this section, the focus is thus on articles considering sustainable transportation, such as electric vehicles (EVs), integrated with the smart grid requirements. As guest editors, we are very pleased to present the selected 12 papers, whose topics are specifically related to optimal planning of charging stations (CSs), sustainable transportation and mobility, EVs integration in smart grids, reliability, reduction of consumption, demand response and smart grid modeling, optimal scheduling, routing and charging of fleets of EVs, as well as smart parking. © 2004-2012 IEEE.},
  keywords = {Energy efficiency; Vehicle-to-grid; Automation engineering; Automation science; Modeling technology; Optimisations; Science and engineering; Smart grid; Special sections; Sustainable energy systems; Sustainable transportation; Sustainable transportation systems; Electric power transmission networks},
  type = {Review},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2; All Open Access, Bronze Open Access}
  }

• Proia, S., Cavone, G., Carli, R. & Dotoli, M. (2022) A Multi-objective Optimization Approach for Trajectory Planning in a Safe and Ergonomic Human-Robot Collaboration IN IEEE International Conference on Automation Science and Engineering., 2068 – 2073. doi:10.1109/CASE49997.2022.9926513
  [BibTeX] [Abstract] [Download PDF]

  In today’s manufacturing companies that rely on Human-Robot Collaboration (HRC), ensuring a safe and ergonomic workplace is becoming of pivotal importance. In a collaborative assembly scenario, this paper aims at planning the trajectory of a collaborative robotic arm, guaranteeing safety and ergonomics for the operator without neglecting production requirements. In particular, a multi-objective optimization approach for the trajectory planning in safe and ergonomic HRC is defined, with the aim of finding the best trade-off between the total traversal time of the trajectory for the robot and ergonomics for the human worker, while respecting safety requirements. The proposed approach consists of three main steps. First, the Rapid Upper Limb Assessment (RULA) ergonomic index is evaluated on a manikin designed on a dedicated software. The aim is to ensure a high quality of work in the considered HRC scenario with a consequent decrease of the musculoskeletal disorders associated with highly repetitive and dangerous activities. Second, a time-optimal and safety-constrained trajectory planning problem is defined as a second-order cone programming problem. Finally, a multi-objective control problem is formulated and solved to compute the trajectory that ensures the best compromise between time end ergonomics. The method is tested on numerical simulations and the obtained results are discussed, proving the effectiveness of the approach. © 2022 IEEE.

  @CONFERENCE{Proia20222068,
  author = {Proia, Silvia and Cavone, Graziana and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A Multi-objective Optimization Approach for Trajectory Planning in a Safe and Ergonomic Human-Robot Collaboration},
  year = {2022},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2022-August},
  pages = {2068 – 2073},
  doi = {10.1109/CASE49997.2022.9926513},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141688471&doi=10.1109%2fCASE49997.2022.9926513&partnerID=40&md5=2fd12a5e7dc0272a9ecfb95dcd756daf},
  abstract = {In today's manufacturing companies that rely on Human-Robot Collaboration (HRC), ensuring a safe and ergonomic workplace is becoming of pivotal importance. In a collaborative assembly scenario, this paper aims at planning the trajectory of a collaborative robotic arm, guaranteeing safety and ergonomics for the operator without neglecting production requirements. In particular, a multi-objective optimization approach for the trajectory planning in safe and ergonomic HRC is defined, with the aim of finding the best trade-off between the total traversal time of the trajectory for the robot and ergonomics for the human worker, while respecting safety requirements. The proposed approach consists of three main steps. First, the Rapid Upper Limb Assessment (RULA) ergonomic index is evaluated on a manikin designed on a dedicated software. The aim is to ensure a high quality of work in the considered HRC scenario with a consequent decrease of the musculoskeletal disorders associated with highly repetitive and dangerous activities. Second, a time-optimal and safety-constrained trajectory planning problem is defined as a second-order cone programming problem. Finally, a multi-objective control problem is formulated and solved to compute the trajectory that ensures the best compromise between time end ergonomics. The method is tested on numerical simulations and the obtained results are discussed, proving the effectiveness of the approach. © 2022 IEEE.},
  author_keywords = {cobots; collaborative robotics; ergonomics; Human-Robot Collaboration (HRC); safety; time-optimal trajectory planning},
  keywords = {Collaborative robots; Economic and social effects; Multiobjective optimization; Numerical methods; Robot programming; Robotic assembly; Trajectories; Collaborative assembly; Ergonomic workplace; Human-robot collaboration; Manufacturing companies; Multi-objectives optimization; Optimization approach; Production requirements; Time-optimal trajectory planning; Trajectory Planning; Ergonomics},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Scarabaggio, P., Carli, R. & Dotoli, M. (2022) Noncooperative Equilibrium-Seeking in Distributed Energy Systems under AC Power Flow Nonlinear Constraints. IN IEEE Transactions on Control of Network Systems, 9.1731 – 1742. doi:10.1109/TCNS.2022.3181527
  [BibTeX] [Abstract] [Download PDF]

  Power distribution grids are commonly controlled through centralized approaches, such as the optimal power flow. However, the current pervasive deployment of distributed renewable energy sources and the increasing growth of active players, providing ancillary services to the grid, have made these centralized frameworks no longer appropriate. In this context, we propose a novel noncooperative control mechanism for optimally regulating the operation of power distribution networks equipped with traditional loads, distributed generation, and active users. The latter, also known as prosumers, contribute to the grid optimization process by leveraging their flexible demand, dispatchable generation capability, and/or energy storage potential. Active users participate in a noncooperative liberalized market designed to increase the penetration of renewable generation and improve the predictability of power injection from the high-voltage grid. The novelty of our game-theoretical approach consists in incorporating economic factors as well as physical constraints and grid stability aspects. Finally, by integrating the proposed framework into a rolling-horizon approach, we show its effectiveness and resiliency through numerical experiments. © 2014 IEEE.

  @ARTICLE{Scarabaggio20221731,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Noncooperative Equilibrium-Seeking in Distributed Energy Systems under AC Power Flow Nonlinear Constraints},
  year = {2022},
  journal = {IEEE Transactions on Control of Network Systems},
  volume = {9},
  number = {4},
  pages = {1731 – 1742},
  doi = {10.1109/TCNS.2022.3181527},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132727510&doi=10.1109%2fTCNS.2022.3181527&partnerID=40&md5=01b1c79aa91772c7e9920d019e70b5b8},
  abstract = {Power distribution grids are commonly controlled through centralized approaches, such as the optimal power flow. However, the current pervasive deployment of distributed renewable energy sources and the increasing growth of active players, providing ancillary services to the grid, have made these centralized frameworks no longer appropriate. In this context, we propose a novel noncooperative control mechanism for optimally regulating the operation of power distribution networks equipped with traditional loads, distributed generation, and active users. The latter, also known as prosumers, contribute to the grid optimization process by leveraging their flexible demand, dispatchable generation capability, and/or energy storage potential. Active users participate in a noncooperative liberalized market designed to increase the penetration of renewable generation and improve the predictability of power injection from the high-voltage grid. The novelty of our game-theoretical approach consists in incorporating economic factors as well as physical constraints and grid stability aspects. Finally, by integrating the proposed framework into a rolling-horizon approach, we show its effectiveness and resiliency through numerical experiments. © 2014 IEEE.},
  author_keywords = {AC power flow; distributed control; electric power networks; game theory},
  keywords = {Distributed parameter control systems; Distributed power generation; Electric load flow; Electric load management; Electric network analysis; Electric power system control; Electric power transmission networks; Natural resources; Renewable energy resources; AC power flow; Distributed energy systems; Distributed-control; Electric power networks; Generator; Load modeling; Network systems; Non-linear constraints; Power grids; Renewable energy source; Game theory},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 34; All Open Access, Green Open Access, Hybrid Gold Open Access}
  }

• Tresca, G., Cavone, G., Carli, R., Cerviotti, A. & Dotoli, M. (2022) Automating Bin Packing: A Layer Building Matheuristics for Cost Effective Logistics. IN IEEE Transactions on Automation Science and Engineering, 19.1599 – 1613. doi:10.1109/TASE.2022.3177422
  [BibTeX] [Abstract] [Download PDF]

  In this paper, we address the problem of automating the definition of feasible pallets configurations. This issue is crucial for the competitiveness of logistic companies and is still one of the most difficult problems in internal logistics. In fact, it requires the fast solution of a three-dimensional Bin Packing Problem (3D-BPP) with additional logistic specifications that are fundamental in real applications. To this aim, we propose a matheuristics that, given a set of items, provides feasible pallets configurations that satisfy the practical requirements of items’ grouping by logistic features, load bearing, stability, height homogeneity, overhang as well as weight limits, and robotized layer picking. The proposed matheuristics combines a mixed integer linear programming (MILP) formulation of the 3D-Single Bin-Size BPP (3D-SBSBPP) and a layer building heuristics. In particular, the feasible pallets configurations are obtained by sequentially solving two MILP sub-problems: the first, given the set of items to be packed, aims at minimizing the unused space in each layer and thus the number of layers; the latter aims at minimizing the number of shipping bins given the set of layers obtained from the first problem. The approach is extensively tested and compared with existing approaches. For its validation we use both realistic data-sets drawn from the literature and real data-sets, obtained from an Italian logistics leader. The resulting outcomes show the effectiveness of the method in providing high-quality bin configurations in short computational times. Note to Practitioners – This work is motivated by the intention of facilitating the transition from Logistics 3.0 to Logistics 4.0 by providing an effective tool to automate bin packing, suitable for automated warehouses. On the one hand, the proposed technique provides stable and compact bin configurations in less than half a minute per bin on average, despite the high computational complexity of the 3D-SBSBPP. On the other hand, the approach allows to consider compatibility constraints for the items (e.g., final customer and category of the items), and the use of robotized layer picking in automated warehouses. In effect, layers composed by only one type of items (i.e., monoitem layers) can be directly picked and placed on the pallet by a robotic arm without the intervention of any operator. Consequently, the adoption of this approach in warehouses could drastically improve the efficiency of the packing process. © 2004-2012 IEEE.

  @ARTICLE{Tresca20221599,
  author = {Tresca, Giulia and Cavone, Graziana and Carli, Raffaele and Cerviotti, Antonio and Dotoli, Mariagrazia},
  title = {Automating Bin Packing: A Layer Building Matheuristics for Cost Effective Logistics},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {3},
  pages = {1599 – 1613},
  doi = {10.1109/TASE.2022.3177422},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131738365&doi=10.1109%2fTASE.2022.3177422&partnerID=40&md5=1c640184f7ba0ceda489906b68da49b9},
  abstract = {In this paper, we address the problem of automating the definition of feasible pallets configurations. This issue is crucial for the competitiveness of logistic companies and is still one of the most difficult problems in internal logistics. In fact, it requires the fast solution of a three-dimensional Bin Packing Problem (3D-BPP) with additional logistic specifications that are fundamental in real applications. To this aim, we propose a matheuristics that, given a set of items, provides feasible pallets configurations that satisfy the practical requirements of items' grouping by logistic features, load bearing, stability, height homogeneity, overhang as well as weight limits, and robotized layer picking. The proposed matheuristics combines a mixed integer linear programming (MILP) formulation of the 3D-Single Bin-Size BPP (3D-SBSBPP) and a layer building heuristics. In particular, the feasible pallets configurations are obtained by sequentially solving two MILP sub-problems: the first, given the set of items to be packed, aims at minimizing the unused space in each layer and thus the number of layers; the latter aims at minimizing the number of shipping bins given the set of layers obtained from the first problem. The approach is extensively tested and compared with existing approaches. For its validation we use both realistic data-sets drawn from the literature and real data-sets, obtained from an Italian logistics leader. The resulting outcomes show the effectiveness of the method in providing high-quality bin configurations in short computational times. Note to Practitioners - This work is motivated by the intention of facilitating the transition from Logistics 3.0 to Logistics 4.0 by providing an effective tool to automate bin packing, suitable for automated warehouses. On the one hand, the proposed technique provides stable and compact bin configurations in less than half a minute per bin on average, despite the high computational complexity of the 3D-SBSBPP. On the other hand, the approach allows to consider compatibility constraints for the items (e.g., final customer and category of the items), and the use of robotized layer picking in automated warehouses. In effect, layers composed by only one type of items (i.e., monoitem layers) can be directly picked and placed on the pallet by a robotic arm without the intervention of any operator. Consequently, the adoption of this approach in warehouses could drastically improve the efficiency of the packing process. © 2004-2012 IEEE.},
  author_keywords = {bin packing; Logistics 4.0; matheuristics; pallets configuration},
  keywords = {Cost effectiveness; Integer programming; Logistics; Pallets; Bin packing; Cost-effective logistics; Fast solutions; Internal Logistics; Logistic 4.0; Logistics company; Matheuristic.; Mixed integer linear; Pallet configuration; Stability criterions; Stability criteria},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 26; All Open Access, Hybrid Gold Open Access}
  }

• Carli, R., Cavone, G., Pippia, T., De Schutter, B. & Dotoli, M. (2022) Robust Optimal Control for Demand Side Management of Multi-Carrier Microgrids. IN IEEE Transactions on Automation Science and Engineering, 19.1338 – 1351. doi:10.1109/TASE.2022.3148856
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on the control of microgrids where both gas and electricity are provided to the final customer, i.e., multi-carrier microgrids. Hence, these microgrids include thermal and electrical loads, renewable energy sources, energy storage systems, heat pumps, and combined heat and power units. The parameters characterizing the multi-carrier microgrid are subject to several disturbances, such as fluctuations in the provision of renewable energy, variability in the electrical and thermal demand, and uncertainties in the electricity and gas pricing. With the aim of accounting for the data uncertainties in the microgrid, we propose a Robust Model Predictive Control (RMPC) approach whose goal is to minimize the total economical cost, while satisfying comfort and energy requests of the final users. In the related literature various RMPC approaches have been proposed, focusing either on electrical or on thermal microgrids. Only a few contributions have addressed the robust control of multi-carrier microgrids. Consequently, we propose an innovative RMPC algorithm that employs on an uncertainty set-based method and that can provide better performance compared with deterministic model predictive controllers applied to multi-carrier microgrids. With the aim of mitigating the conservativeness of the approach, we define suitable robustness factors and we investigate the effects of such factors on the robustness of the solution against variations of the uncertain parameters. We show the effectiveness of the proposed RMPC approach by applying it to a realistic residential multi-carrier microgrid and comparing the obtained results with the ones of a baseline robust method. Note to Practitioners – This work is motivated by the emerging need for effective energy management approaches in multi-carrier microgrids. The inherent difficulty of scheduling simultaneously the operations of various energy infrastructures (e.g., electricity, natural gas) is exacerbated by the inevitable presence of uncertainties that affect the inter-dependent dynamics of different energy resources and equipment. The proposed robust MPC-based control strategy allows the energy manager to effectively determine an optimal energy scheduling of multi-faceted system components, making a tradeoff between performance and protection against data uncertainty. The presented strategy is comprehensive and generic, as it can be applied to different microgrid frameworks integrating various types of system components and sources of uncertainty, while at the same time being implementable in any energy management system. © 2004-2012 IEEE.

  @ARTICLE{Carli20221338,
  author = {Carli, Raffaele and Cavone, Graziana and Pippia, Tomas and De Schutter, Bart and Dotoli, Mariagrazia},
  title = {Robust Optimal Control for Demand Side Management of Multi-Carrier Microgrids},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {3},
  pages = {1338 – 1351},
  doi = {10.1109/TASE.2022.3148856},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124835914&doi=10.1109%2fTASE.2022.3148856&partnerID=40&md5=bba929de55ddb0e8109670e2ef200715},
  abstract = {This paper focuses on the control of microgrids where both gas and electricity are provided to the final customer, i.e., multi-carrier microgrids. Hence, these microgrids include thermal and electrical loads, renewable energy sources, energy storage systems, heat pumps, and combined heat and power units. The parameters characterizing the multi-carrier microgrid are subject to several disturbances, such as fluctuations in the provision of renewable energy, variability in the electrical and thermal demand, and uncertainties in the electricity and gas pricing. With the aim of accounting for the data uncertainties in the microgrid, we propose a Robust Model Predictive Control (RMPC) approach whose goal is to minimize the total economical cost, while satisfying comfort and energy requests of the final users. In the related literature various RMPC approaches have been proposed, focusing either on electrical or on thermal microgrids. Only a few contributions have addressed the robust control of multi-carrier microgrids. Consequently, we propose an innovative RMPC algorithm that employs on an uncertainty set-based method and that can provide better performance compared with deterministic model predictive controllers applied to multi-carrier microgrids. With the aim of mitigating the conservativeness of the approach, we define suitable robustness factors and we investigate the effects of such factors on the robustness of the solution against variations of the uncertain parameters. We show the effectiveness of the proposed RMPC approach by applying it to a realistic residential multi-carrier microgrid and comparing the obtained results with the ones of a baseline robust method. Note to Practitioners - This work is motivated by the emerging need for effective energy management approaches in multi-carrier microgrids. The inherent difficulty of scheduling simultaneously the operations of various energy infrastructures (e.g., electricity, natural gas) is exacerbated by the inevitable presence of uncertainties that affect the inter-dependent dynamics of different energy resources and equipment. The proposed robust MPC-based control strategy allows the energy manager to effectively determine an optimal energy scheduling of multi-faceted system components, making a tradeoff between performance and protection against data uncertainty. The presented strategy is comprehensive and generic, as it can be applied to different microgrid frameworks integrating various types of system components and sources of uncertainty, while at the same time being implementable in any energy management system. © 2004-2012 IEEE.},
  author_keywords = {demand side management (DSM); Energy and environment-aware automation; multi-carrier microgrid; robust model predictive control; robust optimization; set-based uncertainty},
  keywords = {Demand side management; Digital storage; Electric utilities; Heat pump systems; Heat resistance; Heat storage; Model predictive control; Natural resources; Optimization; Random processes; Renewable energy resources; Stochastic systems; Uncertainty analysis; Demand side management; Energy and environment; Energy and environment-aware automation; Heat pumps; Microgrid; Multi-carrier microgrid; Multicarriers; Renewable energy source; Resistance-heating; Robust model predictive control; Robust model predictive control.; Robust optimization; Robustness; Set-based uncertainty; Uncertainty; Robust control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 59; All Open Access, Green Open Access}
  }

• Cavone, G., Bozza, A., Carli, R. & Dotoli, M. (2022) MPC-Based Process Control of Deep Drawing: An Industry 4.0 Case Study in Automotive. IN IEEE Transactions on Automation Science and Engineering, 19.1586 – 1598. doi:10.1109/TASE.2022.3177362
  [BibTeX] [Abstract] [Download PDF]

  Deep drawing is a metalworking procedure aimed at getting a cold metal sheet plastically deformed in accordance with a pre-defined mould. Although this procedure is well-established in industry, it is still susceptible to several issues affecting the quality of the stamped metal products. In order to reduce defects of workpieces, process control approaches can be performed. Typically, process control employs simple proportional-integral-derivative (PID) regulators that steer the blank holder force (BHF) based on the error on the punch force. However, a single PID can only control single-input single-output systems and cannot handle constraints on the process variables. Differently from the state of the art, in this paper we propose a process control architecture based on Model Predictive Control (MPC), which considers a multi-variable system model. In particular, we represent the deep drawing process with a single-input multiple-output Hammerstein-Wiener model that relates the BHF with the draw-in of $n$ different critical points around the die. This allows the avoidance of workpiece defects that are due to the abnormal sliding of the metal sheet during the forming phase. The effectiveness of the proposed process controller is shown on a real case study in a digital twin framework, where the performance achieved by the MPC-based system is analyzed in detail and compared against the results obtained through an ad-hoc defined multiple PID-based control architecture. Note to Practitioners – This work is motivated by the emerging need for the effective implementation of the zero-defect manufacturing paradigm in the Industry 4.0 framework. Especially in the deep drawing process, various quality issues in stamped parts can lead to significant product waste and manufacturing inefficiencies. This turns into considerable economic losses for companies, particularly in the automotive sector, where deep drawing is one of the most used cold sheet metal forming techniques. In most applications, only sample inspections are performed on batches of finished-product, with subsequent losses of time and resources. For the sake of improving the workpiece quality, innovative strategies for real-time process control represent a viable and promising solution. In this context, the proposed MPC-based process control approach allows the correct shaping of the metal sheet that is getting deformed during the forming stroke, thanks to the draw-in monitoring at various locations around the die. The draw-in is indeed one of the most effective forming variables to control in order to provide a correct BHF during the forming stroke. A useful and easy-to-implement non-linear metal sheet deep drawing process model is provided by this paper to perform an innovative process control strategy. A comprehensive methodology is applied in detail to an automotive case study, ranging from process modeling (model identification and validation based on experimental data acquisition) to MPC implementation (controller tuning and testing and software-in-the-loop system validation). The presented method can be easily implemented on any real deep drawing press, providing the multivariable constrained process with a suitable control system able to make the stamped parts well formed. © 2004-2012 IEEE.

  @ARTICLE{Cavone20221586,
  author = {Cavone, Graziana and Bozza, Augusto and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {MPC-Based Process Control of Deep Drawing: An Industry 4.0 Case Study in Automotive},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {3},
  pages = {1586 – 1598},
  doi = {10.1109/TASE.2022.3177362},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131727980&doi=10.1109%2fTASE.2022.3177362&partnerID=40&md5=689e5dd375cab07673634f266a278717},
  abstract = {Deep drawing is a metalworking procedure aimed at getting a cold metal sheet plastically deformed in accordance with a pre-defined mould. Although this procedure is well-established in industry, it is still susceptible to several issues affecting the quality of the stamped metal products. In order to reduce defects of workpieces, process control approaches can be performed. Typically, process control employs simple proportional-integral-derivative (PID) regulators that steer the blank holder force (BHF) based on the error on the punch force. However, a single PID can only control single-input single-output systems and cannot handle constraints on the process variables. Differently from the state of the art, in this paper we propose a process control architecture based on Model Predictive Control (MPC), which considers a multi-variable system model. In particular, we represent the deep drawing process with a single-input multiple-output Hammerstein-Wiener model that relates the BHF with the draw-in of $n$ different critical points around the die. This allows the avoidance of workpiece defects that are due to the abnormal sliding of the metal sheet during the forming phase. The effectiveness of the proposed process controller is shown on a real case study in a digital twin framework, where the performance achieved by the MPC-based system is analyzed in detail and compared against the results obtained through an ad-hoc defined multiple PID-based control architecture. Note to Practitioners - This work is motivated by the emerging need for the effective implementation of the zero-defect manufacturing paradigm in the Industry 4.0 framework. Especially in the deep drawing process, various quality issues in stamped parts can lead to significant product waste and manufacturing inefficiencies. This turns into considerable economic losses for companies, particularly in the automotive sector, where deep drawing is one of the most used cold sheet metal forming techniques. In most applications, only sample inspections are performed on batches of finished-product, with subsequent losses of time and resources. For the sake of improving the workpiece quality, innovative strategies for real-time process control represent a viable and promising solution. In this context, the proposed MPC-based process control approach allows the correct shaping of the metal sheet that is getting deformed during the forming stroke, thanks to the draw-in monitoring at various locations around the die. The draw-in is indeed one of the most effective forming variables to control in order to provide a correct BHF during the forming stroke. A useful and easy-to-implement non-linear metal sheet deep drawing process model is provided by this paper to perform an innovative process control strategy. A comprehensive methodology is applied in detail to an automotive case study, ranging from process modeling (model identification and validation based on experimental data acquisition) to MPC implementation (controller tuning and testing and software-in-the-loop system validation). The presented method can be easily implemented on any real deep drawing press, providing the multivariable constrained process with a suitable control system able to make the stamped parts well formed. © 2004-2012 IEEE.},
  author_keywords = {Metal deep drawing process control; model predictive control; real-time process control; software-in-the-loop simulation; zero-defect manufacturing},
  keywords = {Computer software; Defects; Metal drawing; Metals; Predictive control systems; Proportional control systems; Sheet metal; Two term control systems; Deep-drawing process; Force; Metal deep drawing process control; Model-predictive control; Real-time process control; Software-in-the-loop simulation.; Software-in-the-loop simulations; Uncertainty; Zero defects; Zero-defect manufacturing; Model predictive control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 19; All Open Access, Hybrid Gold Open Access}
  }

• Cavone, G., Carli, R. & Dotoli, M. (2022) Decision and Control Approaches for Enhancing the Resilience of Distribution Networks: a Survey IN IFAC-PapersOnLine., 271 – 276. doi:10.1016/j.ifacol.2023.01.084
  [BibTeX] [Abstract] [Download PDF]

  Recently, the concept of resilience of electrical infrastructures has been introduced to quantify the ability of the grid to resist, adapt to, and rapidly recover after the occurrence of high-impact and low-probability (HILP) events. Various surveys discuss the state of the art on the resilience of distribution networks (DNs), which are a subsystem of the electrical infrastructure particularly susceptible to HILP events. It emerges that automation has a central role in guaranteeing and enhancing DNs resilience, although a classification of the existing contributions is missing. To fill this gap, in this paper we review the literature contributions regarding decision and control methods to enhance the resilience of DNs. We classify the reviewed approaches into tactical/strategic and operational level ones, we group them by the time of application and type, and finally we provide a detailed discussion and comparison of the available methods, highlighting open issues and future trends in this field. Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

  @CONFERENCE{Cavone2022271,
  author = {Cavone, Graziana and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Decision and Control Approaches for Enhancing the Resilience of Distribution Networks: a Survey},
  year = {2022},
  journal = {IFAC-PapersOnLine},
  volume = {55},
  number = {40},
  pages = {271 – 276},
  doi = {10.1016/j.ifacol.2023.01.084},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159328754&doi=10.1016%2fj.ifacol.2023.01.084&partnerID=40&md5=daaa34f2c14722ee40039f3d2c434daf},
  abstract = {Recently, the concept of resilience of electrical infrastructures has been introduced to quantify the ability of the grid to resist, adapt to, and rapidly recover after the occurrence of high-impact and low-probability (HILP) events. Various surveys discuss the state of the art on the resilience of distribution networks (DNs), which are a subsystem of the electrical infrastructure particularly susceptible to HILP events. It emerges that automation has a central role in guaranteeing and enhancing DNs resilience, although a classification of the existing contributions is missing. To fill this gap, in this paper we review the literature contributions regarding decision and control methods to enhance the resilience of DNs. We classify the reviewed approaches into tactical/strategic and operational level ones, we group them by the time of application and type, and finally we provide a detailed discussion and comparison of the available methods, highlighting open issues and future trends in this field. Copyright © 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)},
  author_keywords = {control; decision; Electrical distribution networks; high-impact low-probability events; resilience},
  keywords = {Internet protocols; Control approach; Decision; Electrical distribution networks; Electrical infrastructure; High impact; High impact/low probabilities; High-impact low-probability event; High-low; Lower probabilities; Resilience; Probability distributions},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Gold Open Access}
  }

• Mignoni, N., Scarabaggio, P., Carli, R. & Dotoli, M. (2022) Game Theoretical Control Frameworks for Multiple Energy Storage Services in Energy Communities IN 2022 8th International Conference on Control, Decision and Information Technologies, CoDIT 2022., 1580 – 1585. doi:10.1109/CoDIT55151.2022.9804087
  [BibTeX] [Abstract] [Download PDF]

  In the last decade, distributed energy generation and storage have significantly contributed to the widespread of energy communities. In this context, we propose an energy community model constituted by prosumers, characterized by their own demand and renewable generation, and service-oriented energy storage providers, able to store energy surplus and release it upon a fee payment. We address the problem of optimally schedule the energy flows in the community, with the final goal of making the prosumers’ energy supply more efficient, while creating a sustainable and profitable business model for storage providers. The proposed resolution algorithms are based on decentralized and distributed game theoretical control schemes. These approaches are mathematically formulated and then effectively validated and compared with a centralized method through numerical simulations on realistic scenarios. © 2022 IEEE.

  @CONFERENCE{Mignoni20221580,
  author = {Mignoni, Nicola and Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Game Theoretical Control Frameworks for Multiple Energy Storage Services in Energy Communities},
  year = {2022},
  journal = {2022 8th International Conference on Control, Decision and Information Technologies, CoDIT 2022},
  pages = {1580 – 1585},
  doi = {10.1109/CoDIT55151.2022.9804087},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134303591&doi=10.1109%2fCoDIT55151.2022.9804087&partnerID=40&md5=c5c686570c9998d9639b765af7b24245},
  abstract = {In the last decade, distributed energy generation and storage have significantly contributed to the widespread of energy communities. In this context, we propose an energy community model constituted by prosumers, characterized by their own demand and renewable generation, and service-oriented energy storage providers, able to store energy surplus and release it upon a fee payment. We address the problem of optimally schedule the energy flows in the community, with the final goal of making the prosumers' energy supply more efficient, while creating a sustainable and profitable business model for storage providers. The proposed resolution algorithms are based on decentralized and distributed game theoretical control schemes. These approaches are mathematically formulated and then effectively validated and compared with a centralized method through numerical simulations on realistic scenarios. © 2022 IEEE.},
  keywords = {Game theory; Numerical methods; Community model; Control framework; Demand generation; Distributed energy generation and storages; Energy; Energy flow; Energy supplies; Renewable generation; Service Oriented; Storage services; Energy storage},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M., Shen, W., Jia, S. Q. & Zhong, R. Y. (2022) Special Issue on the 2020 International Conference on Automation Science and Engineering. IN IEEE Transactions on Automation Science and Engineering, 19.1309 – 1311. doi:10.1109/TASE.2022.3180469
  [BibTeX] [Download PDF]

  @ARTICLE{Dotoli20221309,
  author = {Dotoli, Mariagrazia and Shen, Weiming and Jia, Samuel Qing-Shan and Zhong, Ray Y.},
  title = {Special Issue on the 2020 International Conference on Automation Science and Engineering},
  year = {2022},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {19},
  number = {3},
  pages = {1309 – 1311},
  doi = {10.1109/TASE.2022.3180469},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134334978&doi=10.1109%2fTASE.2022.3180469&partnerID=40&md5=441003d09fb42c49c6b1e82ce043c3f4},
  type = {Editorial},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Bronze Open Access}
  }

• Dotoli, M. & Giarré, L. (2022) The 29th Mediterranean Conference on Control and Automation [Conference Reports]. IN IEEE Control Systems, 42.137 – 139. doi:10.1109/MCS.2021.3122770
  [BibTeX] [Download PDF]

  @ARTICLE{Dotoli2022137,
  author = {Dotoli, Mariagrazia and Giarré, Laura},
  title = {The 29th Mediterranean Conference on Control and Automation [Conference Reports]},
  year = {2022},
  journal = {IEEE Control Systems},
  volume = {42},
  number = {1},
  pages = {137 – 139},
  doi = {10.1109/MCS.2021.3122770},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123629711&doi=10.1109%2fMCS.2021.3122770&partnerID=40&md5=b54dd72589254d3b16d0c0c6e3be1531},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Bronze Open Access}
  }

• Hosseini, S. M., Carli, R. & Dotoli, M. (2022) Robust Optimal Demand Response of Energy-efficient Commercial Buildings IN 2022 European Control Conference, ECC 2022., 1606 – 1609. doi:10.23919/ECC55457.2022.9837962
  [BibTeX] [Abstract] [Download PDF]

  Commercial buildings show a great potential for participating in demand response (DR) programs due to their extensive use of energy-intensive flexible loads such as heating, ventilation, and air conditioning (HVAC) systems. The capability of HVAC systems for responding to automated control and intelligent energy scheduling strategies makes them essential flexibility sources in commercial DR. This capability, in combination with the use of local energy storage systems (ESSs), can substantially enhance the energy management performance. This paper proposes a novel robust model predictive control (MPC) approach for online energy scheduling of multiple commercial buildings comprising individual HVAC systems, ESSs, and non-controllable loads. The proposed approach aims at minimizing the total expected energy costs while ensuring the occupants’ thermal comfort under the presence of uncertainties in electricity market pricing. Moreover, operational constraints of the power grid and buildings’ components are considered. To this aim, we firstly formulate the energy scheduling problem as a min-max robust optimization problem which is transformed into a mixed-integer linear programming problem using duality. Next, we apply MPC to solve the robust optimization problem iteratively based on the receding horizon concept. Finally, we assess the performance of the proposed approach on a simulated realistic case study. © 2022 EUCA.

  @CONFERENCE{Hosseini20221606,
  author = {Hosseini, Seyed Mohsen and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Robust Optimal Demand Response of Energy-efficient Commercial Buildings},
  year = {2022},
  journal = {2022 European Control Conference, ECC 2022},
  pages = {1606 – 1609},
  doi = {10.23919/ECC55457.2022.9837962},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136689124&doi=10.23919%2fECC55457.2022.9837962&partnerID=40&md5=b113d8da8b5520d7ef6badc038c033df},
  abstract = {Commercial buildings show a great potential for participating in demand response (DR) programs due to their extensive use of energy-intensive flexible loads such as heating, ventilation, and air conditioning (HVAC) systems. The capability of HVAC systems for responding to automated control and intelligent energy scheduling strategies makes them essential flexibility sources in commercial DR. This capability, in combination with the use of local energy storage systems (ESSs), can substantially enhance the energy management performance. This paper proposes a novel robust model predictive control (MPC) approach for online energy scheduling of multiple commercial buildings comprising individual HVAC systems, ESSs, and non-controllable loads. The proposed approach aims at minimizing the total expected energy costs while ensuring the occupants' thermal comfort under the presence of uncertainties in electricity market pricing. Moreover, operational constraints of the power grid and buildings' components are considered. To this aim, we firstly formulate the energy scheduling problem as a min-max robust optimization problem which is transformed into a mixed-integer linear programming problem using duality. Next, we apply MPC to solve the robust optimization problem iteratively based on the receding horizon concept. Finally, we assess the performance of the proposed approach on a simulated realistic case study. © 2022 EUCA.},
  keywords = {Air conditioning; Costs; Electric energy storage; Electric power transmission networks; Energy efficiency; Model predictive control; Office buildings; Online systems; Optimal control systems; Predictive control systems; Robust control; Scheduling; Commercial building; Conditioning systems; Demand response; Energy; Heating ventilation and air conditioning; Optimization problems; Performance; Response of energy; Robust optimization; Storage systems; Integer programming},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Tresca, G., Cavone, G. & Dotoli, M. (2022) Logistics 4.0: A Matheuristics for the Integrated Vehicle Routing and Container Loading Problem IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 333 – 338. doi:10.1109/SMC53654.2022.9945179
  [BibTeX] [Abstract] [Download PDF]

  The increasing demand for freight transport requires logistic companies to improve their competitiveness by ensuring high service levels at limited costs. This paper investigates the problem of defining delivery plans with the aim to support logistic companies in reducing planning times and freight delivery costs. In delivery planning, given a set of delivery requests, both the routes and load configurations of Transport Units (TUs) are to be established. In the literature, this problem is defined as Three-dimensional Loading Capacitated Vehicle Routing Problem with Time Windows (3LCVRPTW). However, these problems are generally tackled separately and referred to as the vehicle routing problem and the container loading problem, respectively. Moreover, only a few contributions present solution approaches for real logistic systems, and these methods are mainly based on heuristics. In this work, we define a novel matheuristic algorithm for the integrated solution of the vehicle routing problem and container loading problem. The proposed method is suitable for real logistic applications and combines the advantages of exact solutions with the rapidity of heuristics. The approach aims at minimizing the total travel costs and the clients’ time windows violations in the routes’ definition, while optimizing the configuration of the cargo inside each TU. The developed matheuristic algorithm is tested both on a well-known literature benchmark and on a real dataset provided by the Italian company Elettric80. The obtained results show that the proposed method succeeds in determining in a short computational time both feasible routes and loading plans, minimizing the related costs while fulfilling logistics constraints. © 2022 IEEE.

  @CONFERENCE{Tresca2022333,
  author = {Tresca, Giulia and Cavone, Graziana and Dotoli, Mariagrazia},
  title = {Logistics 4.0: A Matheuristics for the Integrated Vehicle Routing and Container Loading Problem},
  year = {2022},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {2022-October},
  pages = {333 – 338},
  doi = {10.1109/SMC53654.2022.9945179},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142707049&doi=10.1109%2fSMC53654.2022.9945179&partnerID=40&md5=d49266c40af796699c225ad073274b31},
  abstract = {The increasing demand for freight transport requires logistic companies to improve their competitiveness by ensuring high service levels at limited costs. This paper investigates the problem of defining delivery plans with the aim to support logistic companies in reducing planning times and freight delivery costs. In delivery planning, given a set of delivery requests, both the routes and load configurations of Transport Units (TUs) are to be established. In the literature, this problem is defined as Three-dimensional Loading Capacitated Vehicle Routing Problem with Time Windows (3LCVRPTW). However, these problems are generally tackled separately and referred to as the vehicle routing problem and the container loading problem, respectively. Moreover, only a few contributions present solution approaches for real logistic systems, and these methods are mainly based on heuristics. In this work, we define a novel matheuristic algorithm for the integrated solution of the vehicle routing problem and container loading problem. The proposed method is suitable for real logistic applications and combines the advantages of exact solutions with the rapidity of heuristics. The approach aims at minimizing the total travel costs and the clients' time windows violations in the routes' definition, while optimizing the configuration of the cargo inside each TU. The developed matheuristic algorithm is tested both on a well-known literature benchmark and on a real dataset provided by the Italian company Elettric80. The obtained results show that the proposed method succeeds in determining in a short computational time both feasible routes and loading plans, minimizing the related costs while fulfilling logistics constraints. © 2022 IEEE.},
  author_keywords = {container loading; logistics; Matheuristics; optimization; vehicle routing},
  keywords = {Containers; Freight transportation; Heuristic methods; Vehicle routing; Vehicles; Container loading; Container-loading problems; Freight transport; Logistics company; Matheuristic; Optimisations; Planning time; Service levels; Transport units; Vehicle Routing Problems; Optimization},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Nasiri, F., Ooka, R., Haghighat, F., Shirzadi, N., Dotoli, M., Carli, R., Scarabaggio, P., Behzadi, A., Rahnama, S., Afshari, A., Kuznik, F., Fabrizio, E., Choudhary, R. & Sadrizadeh, S. (2022) Data Analytics and Information Technologies for Smart Energy Storage Systems: A State-of-the-Art Review. IN Sustainable Cities and Society, 84.. doi:10.1016/j.scs.2022.104004
  [BibTeX] [Abstract] [Download PDF]

  This article provides a state-of-the-art review on emerging applications of smart tools such as data analytics and smart technologies such as internet-of-things in case of design, management and control of energy storage systems. In particular, we have established a classification of the types and targets of various predictive analytics for estimation of load, energy prices, renewable energy inputs, state of the charge, fault diagnosis, etc. In addition, the applications of information technologies, and in particular, use of cloud, internet-of-things, building management systems and building information modeling and their contributions to management of energy storage systems will be reviewed in details. The paper concludes by highlighting the emerging issues in smart energy storage systems and providing directions for future research. © 2022 Elsevier Ltd

  @ARTICLE{Nasiri2022,
  author = {Nasiri, Fuzhan and Ooka, Ryozo and Haghighat, Fariborz and Shirzadi, Navid and Dotoli, Mariagrazia and Carli, Raffaele and Scarabaggio, Paolo and Behzadi, Amirmohammad and Rahnama, Samira and Afshari, Alireza and Kuznik, Frédéric and Fabrizio, Enrico and Choudhary, Ruchi and Sadrizadeh, Sasan},
  title = {Data Analytics and Information Technologies for Smart Energy Storage Systems: A State-of-the-Art Review},
  year = {2022},
  journal = {Sustainable Cities and Society},
  volume = {84},
  doi = {10.1016/j.scs.2022.104004},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133235991&doi=10.1016%2fj.scs.2022.104004&partnerID=40&md5=c1409a9f5cd360d29ca6e0f1bf7f9fe9},
  abstract = {This article provides a state-of-the-art review on emerging applications of smart tools such as data analytics and smart technologies such as internet-of-things in case of design, management and control of energy storage systems. In particular, we have established a classification of the types and targets of various predictive analytics for estimation of load, energy prices, renewable energy inputs, state of the charge, fault diagnosis, etc. In addition, the applications of information technologies, and in particular, use of cloud, internet-of-things, building management systems and building information modeling and their contributions to management of energy storage systems will be reviewed in details. The paper concludes by highlighting the emerging issues in smart energy storage systems and providing directions for future research. © 2022 Elsevier Ltd},
  author_keywords = {Artificial Intelligence; Data Analytics; Energy Storage; Information Technology; Renewable Energy Intermittency; Smart Systems},
  keywords = {Classification (of information); Digital storage; Energy storage; Information management; Internet of things; Predictive analytics; Data analytics; Data informations; Emerging applications; Intermittency; Renewable energies; Renewable energy intermittency; Smart energies; Smart System; State-of-the art reviews; Storage systems; alternative energy; artificial intelligence; data processing; design; energy storage; information technology; Data Analytics},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 12}
  }

• Tong, Y., Xu, W., Dotoli, M. & Cavone, G. (2022) An Integrated Model Predictive Control Method for the Rescheduling of Metro Traffic with Backup Trains IN Proceedings of the American Control Conference., 4648 – 4653. doi:10.23919/ACC53348.2022.9867359
  [BibTeX] [Abstract] [Download PDF]

  In large cities, metro lines are often saturated and impacted by sudden events to the point that some stations in the network become overcrowded and multiple trains are seriously delayed, causing the increase of passengers’ waiting time. This disservice can be reduced by rescheduling the metro traffic and by adding backup trains in storage lines to be used when the service level largely decreases. In this paper, a novel control strategy, called Integrated Model Predictive Control, is proposed that combines both timetable rescheduling and backup trains allocation. In particular, a state-space model is adopted to describe the evolution of the train traffic dynamics and the model predictive control method is applied to obtain an optimal controller such that the rescheduled departure time and headway deviations from the nominal timetable are minimized. In the case where no feasible controller exists because of extensive delays, we propose an event-triggered process to automatically add backup trains into the operation plan such that the timetable can recover quickly. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed control method. © 2022 American Automatic Control Council.

  @CONFERENCE{Tong20224648,
  author = {Tong, Yin and Xu, Wei and Dotoli, Mariagrazia and Cavone, Graziana},
  title = {An Integrated Model Predictive Control Method for the Rescheduling of Metro Traffic with Backup Trains},
  year = {2022},
  journal = {Proceedings of the American Control Conference},
  volume = {2022-June},
  pages = {4648 – 4653},
  doi = {10.23919/ACC53348.2022.9867359},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138491731&doi=10.23919%2fACC53348.2022.9867359&partnerID=40&md5=5cf99d9b147f7d3a0a367b3e01422414},
  abstract = {In large cities, metro lines are often saturated and impacted by sudden events to the point that some stations in the network become overcrowded and multiple trains are seriously delayed, causing the increase of passengers' waiting time. This disservice can be reduced by rescheduling the metro traffic and by adding backup trains in storage lines to be used when the service level largely decreases. In this paper, a novel control strategy, called Integrated Model Predictive Control, is proposed that combines both timetable rescheduling and backup trains allocation. In particular, a state-space model is adopted to describe the evolution of the train traffic dynamics and the model predictive control method is applied to obtain an optimal controller such that the rescheduled departure time and headway deviations from the nominal timetable are minimized. In the case where no feasible controller exists because of extensive delays, we propose an event-triggered process to automatically add backup trains into the operation plan such that the timetable can recover quickly. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed control method. © 2022 American Automatic Control Council.},
  keywords = {Controllers; Numerical methods; Railroad transportation; Railroads; Scheduling; State space methods; Control strategies; Integrated model predictive control; Large cities; Metro lines; Metro traffics; Multiple trains; Passenger waiting time; Predictive control methods; Service levels; Sudden events; Model predictive control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

2021

• Cavone, G., Epicoco, N., Carli, R., Del Zotti, A., Paulo Ribeiro Pereira, J. & Dotoli, M. (2021) Parcel delivery with drones: Multi-criteria analysis of trendy system architectures IN 2021 29th Mediterranean Conference on Control and Automation, MED 2021., 693 – 698. doi:10.1109/MED51440.2021.9480332
  [BibTeX] [Abstract] [Download PDF]

  New technologies, such as Unmanned Aerial Vehicles (UAVs), are transforming facilities and vehicles into intelligent systems that will significantly modify logistic deliveries in any organization. With the appearance of automated vehicles, drones offer multiple new technological solutions that might trigger different delivery networks or boost new delivery services. Differently from the related works, where a single specific delivery system model is typically addressed, this paper deals with the use of UAVs for logistic deliveries focusing on a multi-criteria analysis of trendy drone-based system architectures. In particular, using the cross-efficiency Data Envelopment Analysis approach, a comparative analysis among three different delivery systems is performed: the classic system based on trucks only, the drone-only system using a fleet of drones, and the hybrid truck and drone system combining trucks and drones. The proposed technique constitutes an effective decision-making tool aimed at helping delivery companies in selecting the optimal delivery system architecture according to their specific needs. The effectiveness of the proposed methodology is shown by a simulation analysis based on a realistic data case study that pertains to the main logistic service providers. © 2021 IEEE.

  @CONFERENCE{Cavone2021693,
  author = {Cavone, Graziana and Epicoco, Nicola and Carli, Raffaele and Del Zotti, Anna and Paulo Ribeiro Pereira, Joao and Dotoli, Mariagrazia},
  title = {Parcel delivery with drones: Multi-criteria analysis of trendy system architectures},
  year = {2021},
  journal = {2021 29th Mediterranean Conference on Control and Automation, MED 2021},
  pages = {693 – 698},
  doi = {10.1109/MED51440.2021.9480332},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113688309&doi=10.1109%2fMED51440.2021.9480332&partnerID=40&md5=b1147e916948e156664d7ff61520c1dd},
  abstract = {New technologies, such as Unmanned Aerial Vehicles (UAVs), are transforming facilities and vehicles into intelligent systems that will significantly modify logistic deliveries in any organization. With the appearance of automated vehicles, drones offer multiple new technological solutions that might trigger different delivery networks or boost new delivery services. Differently from the related works, where a single specific delivery system model is typically addressed, this paper deals with the use of UAVs for logistic deliveries focusing on a multi-criteria analysis of trendy drone-based system architectures. In particular, using the cross-efficiency Data Envelopment Analysis approach, a comparative analysis among three different delivery systems is performed: the classic system based on trucks only, the drone-only system using a fleet of drones, and the hybrid truck and drone system combining trucks and drones. The proposed technique constitutes an effective decision-making tool aimed at helping delivery companies in selecting the optimal delivery system architecture according to their specific needs. The effectiveness of the proposed methodology is shown by a simulation analysis based on a realistic data case study that pertains to the main logistic service providers. © 2021 IEEE.},
  author_keywords = {Data Envelopment Analysis; Drones; Multi-criteria decision making; Parcel delivery; UAVs},
  keywords = {Antennas; Automation; Automobiles; Data envelopment analysis; Decision making; Drones; Fleet operations; Intelligent systems; Network architecture; Trucks; Automated vehicles; Comparative analysis; Decision making tool; Logistic services; Multi Criteria Analysis; Simulation analysis; System architectures; Technological solution; Computer architecture},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 12; All Open Access, Green Open Access}
  }

• Cavone, G., Carli, R., Troccoli, G., Tresca, G. & Dotoli, M. (2021) A MILP approach for the multi-drop container loading problem resolution in logistics 4.0 IN 2021 29th Mediterranean Conference on Control and Automation, MED 2021., 687 – 692. doi:10.1109/MED51440.2021.9480359
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses the multi-drop container loading problem (CLP), i.e., the problem of packing multiple bins -associated to multiple deliveries to one or more customers- into a finite number of transport units (TUs). Differently from the traditional CLP, the multi-drop CLP has been rarely handled in the literature, while effective algorithms to automatically solve this problem are needed to improve the efficiency and sustainability of internal logistics. To this aim, we propose a novel algorithm that solves a delivery-based mixed integer linear programming formulation of the problem. The algorithm efficiently determines the optimal composition of TUs by minimizing the unused space, while fulfilling a set of geometric and safety constraints, and complying with the delivery allocation. In particular, the proposed algorithm includes two steps: the first aims at clustering bins into groups to be compatibly loaded in various TUs; the latter aims at determining the optimal configuration of each group in the related TU. Finally, the proposed algorithm is applied to several realistic case studies with the aim of testing and analysing its effectiveness in producing stable and compact TU loading configurations in a short computation time, despite the high computational complexity of the multi-drop CLP. © 2021 IEEE.

  @CONFERENCE{Cavone2021687,
  author = {Cavone, Graziana and Carli, Raffaele and Troccoli, Giorgio and Tresca, Giulia and Dotoli, Mariagrazia},
  title = {A MILP approach for the multi-drop container loading problem resolution in logistics 4.0},
  year = {2021},
  journal = {2021 29th Mediterranean Conference on Control and Automation, MED 2021},
  pages = {687 – 692},
  doi = {10.1109/MED51440.2021.9480359},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113699292&doi=10.1109%2fMED51440.2021.9480359&partnerID=40&md5=734929101ce82724d3629ddb1e06f4a4},
  abstract = {This paper addresses the multi-drop container loading problem (CLP), i.e., the problem of packing multiple bins -associated to multiple deliveries to one or more customers- into a finite number of transport units (TUs). Differently from the traditional CLP, the multi-drop CLP has been rarely handled in the literature, while effective algorithms to automatically solve this problem are needed to improve the efficiency and sustainability of internal logistics. To this aim, we propose a novel algorithm that solves a delivery-based mixed integer linear programming formulation of the problem. The algorithm efficiently determines the optimal composition of TUs by minimizing the unused space, while fulfilling a set of geometric and safety constraints, and complying with the delivery allocation. In particular, the proposed algorithm includes two steps: the first aims at clustering bins into groups to be compatibly loaded in various TUs; the latter aims at determining the optimal configuration of each group in the related TU. Finally, the proposed algorithm is applied to several realistic case studies with the aim of testing and analysing its effectiveness in producing stable and compact TU loading configurations in a short computation time, despite the high computational complexity of the multi-drop CLP. © 2021 IEEE.},
  author_keywords = {Container loading problem; Logistics; MILP; Multi-drop; Optimization},
  keywords = {Bins; Drops; Integer programming; Container-loading problems; Effective algorithms; Internal Logistics; Loading configuration; Mixed integer linear programming; Multiple deliveries; Optimal composition; Safety constraint; Clustering algorithms},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 5}
  }

• Atrigna, M., Buonanno, A., Carli, R., Cavone, G., Scarabaggio, P., Valenti, M., Graditi, G. & Dotoli, M. (2021) Effects of Heatwaves on the Failure of Power Distribution Grids: A Fault Prediction System Based on Machine Learning IN 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 – Proceedings.. doi:10.1109/EEEIC/ICPSEurope51590.2021.9584751
  [BibTeX] [Abstract] [Download PDF]

  Nowadays, a power system failure can drastically affect the reliability and normal operation of power distribution grids. The preparation for these failure events is currently approached with post-event analysis to identify the area of the system that requires the most resources in order to prevent future failures. Nevertheless, the forecasting of such events can be useful to anticipate the failure and possibly avoid it. In this work, we employ several machine learning approaches to analyze historical failure data and predict power grid outages based on operational and meteorological data. The approach is tested with real failure data of a power distribution network in the South of Italy, demonstrating advantageous results also to determine areas requiring particular attention. © 2021 IEEE

  @CONFERENCE{Atrigna2021,
  author = {Atrigna, Mauro and Buonanno, Amedeo and Carli, Raffaele and Cavone, Graziana and Scarabaggio, Paolo and Valenti, Maria and Graditi, Giorgio and Dotoli, Mariagrazia},
  title = {Effects of Heatwaves on the Failure of Power Distribution Grids: A Fault Prediction System Based on Machine Learning},
  year = {2021},
  journal = {21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings},
  doi = {10.1109/EEEIC/ICPSEurope51590.2021.9584751},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126456706&doi=10.1109%2fEEEIC%2fICPSEurope51590.2021.9584751&partnerID=40&md5=fc9788f00e259fdaabf0cb50c06253be},
  abstract = {Nowadays, a power system failure can drastically affect the reliability and normal operation of power distribution grids. The preparation for these failure events is currently approached with post-event analysis to identify the area of the system that requires the most resources in order to prevent future failures. Nevertheless, the forecasting of such events can be useful to anticipate the failure and possibly avoid it. In this work, we employ several machine learning approaches to analyze historical failure data and predict power grid outages based on operational and meteorological data. The approach is tested with real failure data of a power distribution network in the South of Italy, demonstrating advantageous results also to determine areas requiring particular attention. © 2021 IEEE},
  author_keywords = {machine learning; Power system failures; Power system reliability},
  keywords = {Electric power transmission networks; Failure (mechanical); Forecasting; Machine learning; Meteorology; Systems engineering; Failure data; Fault prediction; Heatwaves; Machine-learning; Normal operations; On-machines; Power distribution grids; Power system failures; Power systems reliability; Prediction systems; Outages},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 4}
  }

• Calefati, M., Proia, S., Scarabaggio, P., Carli, R. & Dotoli, M. (2021) A Decentralized Noncooperative Control Approach for Sharing Energy Storage Systems in Energy Communities IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 1430 – 1435. doi:10.1109/SMC52423.2021.9658851
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on the optimal scheduling of the charging and discharging strategies of a community energy storage (CES) system, which is shared by the prosumers belonging to a grid-connected energy community. The prosumers own renewable energy sources (RESs), while they can buy/sell their energy imbalance directly from/to the power grid. For the sake of increasing the penetration of RESs and reducing the operating cost, prosumers leverage on the shared CES: in particular, each user can only employ a portion of the overall CES charge/discharge profile. Differently from the related literature, where storage devices are individually owned and the battery degradation aspects are typically disregarded, we propose a novel control mechanism based on noncooperative game theory, which allows users to minimize their energy cost as well as concur on the CES resources allocation with minimal-degradation. The effectiveness of the method is validated through numerical experiments on a realistic case study, where a shared CES supplies energy to the local community of residential prosumers. Finally, the comparison with a centralized control approach shows that the proposed framework allows all prosumers to achieve a fair cost-optimal utilization of the shared CES. © 2021 IEEE.

  @CONFERENCE{Calefati20211430,
  author = {Calefati, Marino and Proia, Silvia and Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A Decentralized Noncooperative Control Approach for Sharing Energy Storage Systems in Energy Communities},
  year = {2021},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  pages = {1430 – 1435},
  doi = {10.1109/SMC52423.2021.9658851},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124302216&doi=10.1109%2fSMC52423.2021.9658851&partnerID=40&md5=9472abc4fceb04dd351c66a9d3b2a30b},
  abstract = {This paper focuses on the optimal scheduling of the charging and discharging strategies of a community energy storage (CES) system, which is shared by the prosumers belonging to a grid-connected energy community. The prosumers own renewable energy sources (RESs), while they can buy/sell their energy imbalance directly from/to the power grid. For the sake of increasing the penetration of RESs and reducing the operating cost, prosumers leverage on the shared CES: in particular, each user can only employ a portion of the overall CES charge/discharge profile. Differently from the related literature, where storage devices are individually owned and the battery degradation aspects are typically disregarded, we propose a novel control mechanism based on noncooperative game theory, which allows users to minimize their energy cost as well as concur on the CES resources allocation with minimal-degradation. The effectiveness of the method is validated through numerical experiments on a realistic case study, where a shared CES supplies energy to the local community of residential prosumers. Finally, the comparison with a centralized control approach shows that the proposed framework allows all prosumers to achieve a fair cost-optimal utilization of the shared CES. © 2021 IEEE.},
  author_keywords = {decentralized control; energy community; energy storage; game theory; noncooperative control},
  keywords = {Decentralized control; Electric power transmission networks; Energy storage; Numerical methods; Renewable energy resources; Smart power grids; Virtual storage; Community energy; Control approach; Decentralised; Decentralised control; Energy; Energy community; Noncooperative control; Optimal scheduling; Renewable energy source; Storage systems; Game theory},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Scarabaggio, P., Carli, R., Jantzen, J. & Dotoli, M. (2021) Stochastic model predictive control of community energy storage under high renewable penetration IN 2021 29th Mediterranean Conference on Control and Automation, MED 2021., 973 – 978. doi:10.1109/MED51440.2021.9480353
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on the robust optimal on-line scheduling of a grid-connected energy community, where users are equipped with non-controllable (NCLs) and controllable loads (CLs) and share renewable energy sources (RESs) and a community energy storage system (CESS). Leveraging on the pricing signals gathered from the power grid and the predicted values for local production and demand, the energy activities inside the community are decided by a community energy manager. Differently from literature contributions commonly focused on deterministic optimal control schemes, to cope with the uncertainty that affects the forecast of the inflexible demand profile and the renewable production curve, we propose a Stochastic Model Predictive Control (MPC) approach aimed at minimizing the community energy costs. The effectiveness of the method is validated through numerical experiments on the marina of Ballen, Samso (Denmark). The comparison with a standard deterministic optimal control approach shows that the proposed stochastic MPC achieves higher performance in terms of minimized energy cost and maximized self-consumption of on-site production. © 2021 IEEE.

  @CONFERENCE{Scarabaggio2021973,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Jantzen, Jan and Dotoli, Mariagrazia},
  title = {Stochastic model predictive control of community energy storage under high renewable penetration},
  year = {2021},
  journal = {2021 29th Mediterranean Conference on Control and Automation, MED 2021},
  pages = {973 – 978},
  doi = {10.1109/MED51440.2021.9480353},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113644274&doi=10.1109%2fMED51440.2021.9480353&partnerID=40&md5=6156faadbaf382124749771a715a60df},
  abstract = {This paper focuses on the robust optimal on-line scheduling of a grid-connected energy community, where users are equipped with non-controllable (NCLs) and controllable loads (CLs) and share renewable energy sources (RESs) and a community energy storage system (CESS). Leveraging on the pricing signals gathered from the power grid and the predicted values for local production and demand, the energy activities inside the community are decided by a community energy manager. Differently from literature contributions commonly focused on deterministic optimal control schemes, to cope with the uncertainty that affects the forecast of the inflexible demand profile and the renewable production curve, we propose a Stochastic Model Predictive Control (MPC) approach aimed at minimizing the community energy costs. The effectiveness of the method is validated through numerical experiments on the marina of Ballen, Samso (Denmark). The comparison with a standard deterministic optimal control approach shows that the proposed stochastic MPC achieves higher performance in terms of minimized energy cost and maximized self-consumption of on-site production. © 2021 IEEE.},
  author_keywords = {Community energy storage; Community renewables; Energy community; Energy management; On-line energy scheduling; Stochastic model predictive control},
  keywords = {Electric power transmission networks; Energy storage; Model predictive control; Numerical methods; Optimization; Predictive control systems; Renewable energy resources; Stochastic control systems; Stochastic systems; Comparison with a standard; Controllable loads; Local production; Numerical experiments; On-site production; Online scheduling; Optimal control scheme; Renewable energy source; Stochastic models},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Luo, J., Tong, Y., Cavone, G. & Dotoli, M. (2021) A Service-Oriented Metro Traffic Regulation Method for Improving Operation Performance IN IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC., 3533 – 3538. doi:10.1109/ITSC48978.2021.9564503
  [BibTeX] [Abstract] [Download PDF]

  For high density metro traffic, nowadays the time-variant passenger flow is the main cause of train delays and stranded passengers. In this work a novel framework that integrates a passenger flow module (PFM) and a train operation module (TOM) is proposed with the aim of simultaneously minimizing traffic delays and passengers’ discomfort. The two modules interact with each other so that the headway time is automatically adjusted when a platform is overcrowded, and the train traffic is immediately regulated according to the new headway time. As a result, the number of passengers on the platform and their total waiting time can be significantly reduced. Numerical results are provided to show the effectiveness of the proposed method in improving the operation performance while minimizing the passengers’ discomfort. © 2021 IEEE.

  @CONFERENCE{Luo20213533,
  author = {Luo, Jiate and Tong, Yin and Cavone, Graziana and Dotoli, Mariagrazia},
  title = {A Service-Oriented Metro Traffic Regulation Method for Improving Operation Performance},
  year = {2021},
  journal = {IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC},
  volume = {2021-September},
  pages = {3533 – 3538},
  doi = {10.1109/ITSC48978.2021.9564503},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118448237&doi=10.1109%2fITSC48978.2021.9564503&partnerID=40&md5=75a73b3639d1cc8614a800ad9d1f66bb},
  abstract = {For high density metro traffic, nowadays the time-variant passenger flow is the main cause of train delays and stranded passengers. In this work a novel framework that integrates a passenger flow module (PFM) and a train operation module (TOM) is proposed with the aim of simultaneously minimizing traffic delays and passengers' discomfort. The two modules interact with each other so that the headway time is automatically adjusted when a platform is overcrowded, and the train traffic is immediately regulated according to the new headway time. As a result, the number of passengers on the platform and their total waiting time can be significantly reduced. Numerical results are provided to show the effectiveness of the proposed method in improving the operation performance while minimizing the passengers' discomfort. © 2021 IEEE.},
  keywords = {A-train; Metro traffics; Operation performance; Passenger discomfort; Passenger flows; Service Oriented; Time variant; Traffic regulations; Train delay; Train operations; Numerical methods},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6; All Open Access, Green Open Access}
  }

• Bozza, A., Cavone, G., Carli, R., Mazzoccoli, L. & Dotoli, M. (2021) An MPC-based Approach for the Feedback Control of the Cold Sheet Metal Forming Process IN IEEE International Conference on Automation Science and Engineering., 286 – 291. doi:10.1109/CASE49439.2021.9551602
  [BibTeX] [Abstract] [Download PDF]

  In the automotive sector the cold forming of metal sheets is one of the main production activities. However, it is also one of the main source of production wastes. The generally adopted strategy to reduce the number of abnormal stamped parts is the feedback control of the stamping press (i.e., the machine control), while the feedback control of the stamping process is rarely considered. The process control, differently from the press control, can allow the monitoring of the state of the stamped part during the formation phase and the provision of corrective actions in case of abnormal behaviors of the metal sheet, thus ensuring a more precise control of the process. In this context, this paper presents a novel methodology for the cold metal forming process control based on Model Predictive Control (MPC). Firstly, a dynamical model of the system is defined that describes the draw-in of n critical points of the metal sheet as a function of the Blank Holder Force (BHF) and the punch stroke. Then, two different MPC-based real-time controllers are built for two different types of press configuration: the monolithic and the differential one. In the first case, a mono-MPC control system evaluates the draw-in of n critical points and computes a single couple of control signals (i.e., the BHF and the punch stroke). In the second case, a multi-MPC control system computes n different couples of control signals, i.e., one for each monitored draw-in. Finally, a case study is presented with the aim to test both the architectures, considering several simulation scenarios (with or without external disturbances on the plant), in order to make a control system architectures comparison in terms of tracking errors and workpiece quality. © 2021 IEEE.

  @CONFERENCE{Bozza2021286,
  author = {Bozza, Augusto and Cavone, Graziana and Carli, Raffaele and Mazzoccoli, Luigi and Dotoli, Mariagrazia},
  title = {An MPC-based Approach for the Feedback Control of the Cold Sheet Metal Forming Process},
  year = {2021},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2021-August},
  pages = {286 – 291},
  doi = {10.1109/CASE49439.2021.9551602},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117041530&doi=10.1109%2fCASE49439.2021.9551602&partnerID=40&md5=8f6b0f6133565ad0c087ea675cf9c3b9},
  abstract = {In the automotive sector the cold forming of metal sheets is one of the main production activities. However, it is also one of the main source of production wastes. The generally adopted strategy to reduce the number of abnormal stamped parts is the feedback control of the stamping press (i.e., the machine control), while the feedback control of the stamping process is rarely considered. The process control, differently from the press control, can allow the monitoring of the state of the stamped part during the formation phase and the provision of corrective actions in case of abnormal behaviors of the metal sheet, thus ensuring a more precise control of the process. In this context, this paper presents a novel methodology for the cold metal forming process control based on Model Predictive Control (MPC). Firstly, a dynamical model of the system is defined that describes the draw-in of n critical points of the metal sheet as a function of the Blank Holder Force (BHF) and the punch stroke. Then, two different MPC-based real-time controllers are built for two different types of press configuration: the monolithic and the differential one. In the first case, a mono-MPC control system evaluates the draw-in of n critical points and computes a single couple of control signals (i.e., the BHF and the punch stroke). In the second case, a multi-MPC control system computes n different couples of control signals, i.e., one for each monitored draw-in. Finally, a case study is presented with the aim to test both the architectures, considering several simulation scenarios (with or without external disturbances on the plant), in order to make a control system architectures comparison in terms of tracking errors and workpiece quality. © 2021 IEEE.},
  author_keywords = {Metal forming; Model Predictive Control; process control; real-time feedback control},
  keywords = {Automotive industry; Feedback control; Metal forming; Metals; Predictive control systems; Presses (machine tools); Sheet metal; Stamping; Blank holder forces; Cold sheets; Control signal; Draw-in; Metal-forming process; Model-predictive control; Punch stroke; Real-time feedback; Real-time feedback control; Sheet metal forming; Model predictive control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

• Hosseini, S. M., Carli, R. & Dotoli, M. (2021) Robust Optimal Energy Management of a Residential Microgrid under Uncertainties on Demand and Renewable Power Generation. IN IEEE Transactions on Automation Science and Engineering, 18.618 – 637. doi:10.1109/TASE.2020.2986269
  [BibTeX] [Abstract] [Download PDF]

  Smart microgrids are experiencing an increasing growth due to their economic, social, and environmental benefits. However, the inherent intermittency of renewable energy sources (RESs) and users’ behavior lead to significant uncertainty, which implies important challenges on the system design. Facing this issue, this article proposes a novel robust framework for the day-ahead energy scheduling of a residential microgrid comprising interconnected smart users, each owning individual RESs, noncontrollable loads (NCLs), energy- and comfort-based CLs, and individual plug-in electric vehicles (PEVs). Moreover, users share a number of RESs and an energy storage system (ESS). We assume that the microgrid can buy/sell energy from/to the grid subject to quadratic/linear dynamic pricing functions. The objective of scheduling is minimizing the expected energy cost while satisfying device/comfort/contractual constraints, including feasibility constraints on energy transfer between users and the grid under RES generation and users’ demand uncertainties. To this aim, first, we formulate a min-max robust problem to obtain the optimal CLs scheduling and charging/discharging strategies of the ESS and PEVs. Then, based on the duality theory for multi-objective optimization, we transform the min-max problem into a mixed-integer quadratic programming problem to solve the equivalent robust counterpart of the scheduling problem effectively. We deal with the conservativeness of the proposed approach for different scenarios and quantify the effects of the budget of uncertainty on the cost saving, the peak-to-average ratio, and the constraints’ violation rate. We validate the effectiveness of the method on a simulated case study and we compare the results with a related robust approach. Note to Practitioners – This article is motivated by the emerging need for intelligent demand-side management (DSM) approaches in smart microgrids in the presence of both power generation and demand uncertainties. The proposed robust energy scheduling strategy allows the decision maker (i.e., the energy manager of the microgrid) to make a satisfactory tradeoff between the users’ payment and constraints’ violation rate considering the energy cost saving, the system technical limitations and the users’ comfort by adjusting the values of the budget of uncertainty. The proposed framework is generic and flexible as it can be applied to different structures of microgrids considering various types of uncertainties in energy generation or demand. © 2004-2012 IEEE.

  @ARTICLE{Hosseini2021618,
  author = {Hosseini, Seyed Mohsen and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Robust Optimal Energy Management of a Residential Microgrid under Uncertainties on Demand and Renewable Power Generation},
  year = {2021},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {18},
  number = {2},
  pages = {618 – 637},
  doi = {10.1109/TASE.2020.2986269},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100266630&doi=10.1109%2fTASE.2020.2986269&partnerID=40&md5=ab5c0a8a4eb48977e42d7186b3d4fc3b},
  abstract = {Smart microgrids are experiencing an increasing growth due to their economic, social, and environmental benefits. However, the inherent intermittency of renewable energy sources (RESs) and users' behavior lead to significant uncertainty, which implies important challenges on the system design. Facing this issue, this article proposes a novel robust framework for the day-ahead energy scheduling of a residential microgrid comprising interconnected smart users, each owning individual RESs, noncontrollable loads (NCLs), energy- and comfort-based CLs, and individual plug-in electric vehicles (PEVs). Moreover, users share a number of RESs and an energy storage system (ESS). We assume that the microgrid can buy/sell energy from/to the grid subject to quadratic/linear dynamic pricing functions. The objective of scheduling is minimizing the expected energy cost while satisfying device/comfort/contractual constraints, including feasibility constraints on energy transfer between users and the grid under RES generation and users' demand uncertainties. To this aim, first, we formulate a min-max robust problem to obtain the optimal CLs scheduling and charging/discharging strategies of the ESS and PEVs. Then, based on the duality theory for multi-objective optimization, we transform the min-max problem into a mixed-integer quadratic programming problem to solve the equivalent robust counterpart of the scheduling problem effectively. We deal with the conservativeness of the proposed approach for different scenarios and quantify the effects of the budget of uncertainty on the cost saving, the peak-to-average ratio, and the constraints' violation rate. We validate the effectiveness of the method on a simulated case study and we compare the results with a related robust approach. Note to Practitioners - This article is motivated by the emerging need for intelligent demand-side management (DSM) approaches in smart microgrids in the presence of both power generation and demand uncertainties. The proposed robust energy scheduling strategy allows the decision maker (i.e., the energy manager of the microgrid) to make a satisfactory tradeoff between the users' payment and constraints' violation rate considering the energy cost saving, the system technical limitations and the users' comfort by adjusting the values of the budget of uncertainty. The proposed framework is generic and flexible as it can be applied to different structures of microgrids considering various types of uncertainties in energy generation or demand. © 2004-2012 IEEE.},
  author_keywords = {Demand-side management (DSM); microgrid; mixed-integer quadratic programming (MIQP); optimal energy scheduling; optimization; robust control},
  keywords = {Budget control; Costs; Decision making; Electric utilities; Electromagnetic wave emission; Energy storage; Energy transfer; Housing; Integer programming; Microgrids; Multiobjective optimization; Plug-in electric vehicles; Quadratic programming; Renewable energy resources; Scheduling; Energy storage systems; Environmental benefits; Mixed integer quadratic programming; Peak to average ratios; Renewable energy source; Renewable power generation; Scheduling strategies; Technical limitations; Demand side management},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 147}
  }

• Scarabaggio, P., Carli, R., Cavone, G., Epicoco, N. & Dotoli, M. (2021) Modeling, estimation, and analysis of COVID-19 secondary waves: The Case of the Italian Country IN 2021 29th Mediterranean Conference on Control and Automation, MED 2021., 794 – 800. doi:10.1109/MED51440.2021.9480319
  [BibTeX] [Abstract] [Download PDF]

  The recent trends of the COVID-19 research have been devoted to disease transmission modeling, with the aim of investigating the effects of different mitigation strategies mainly through scenario-based simulations. In this context we propose a novel non-linear time-varying model that effectively supports policy-makers in predicting and analyzing the dynamics of COVID-19 secondary waves. Specifically, this paper proposes an accurate SIRUCQTHE epidemiological model to get reliable predictions on the pandemic dynamics. Differently from the related literature, in the fitting phase, we make use of the google mobility reports to identify and predict the evolution of the infection rate. The effectiveness of the presented method is tested on the network of Italian regions. First, we describe the Italian epidemiological scenario in the COVID-19 second wave of contagions, showing the raw data available for the Italian scenario and discussing the main assumptions on the system parameters. Then, we present the different steps of the procedure used for the dynamical fitting of the SIRUCQTHE model. Finally, we compare the estimation results with the real data on the COVID-19 secondary waves in Italy. Provided the availability of reliable data to calibrate the model in heterogeneous scenarios, the proposed approach can be easily extended to cope with other scenarios. © 2021 IEEE.

  @CONFERENCE{Scarabaggio2021794,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Cavone, Graziana and Epicoco, Nicola and Dotoli, Mariagrazia},
  title = {Modeling, estimation, and analysis of COVID-19 secondary waves: The Case of the Italian Country},
  year = {2021},
  journal = {2021 29th Mediterranean Conference on Control and Automation, MED 2021},
  pages = {794 – 800},
  doi = {10.1109/MED51440.2021.9480319},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113602900&doi=10.1109%2fMED51440.2021.9480319&partnerID=40&md5=980feaa724975719c46c214ad1dcbfed},
  abstract = {The recent trends of the COVID-19 research have been devoted to disease transmission modeling, with the aim of investigating the effects of different mitigation strategies mainly through scenario-based simulations. In this context we propose a novel non-linear time-varying model that effectively supports policy-makers in predicting and analyzing the dynamics of COVID-19 secondary waves. Specifically, this paper proposes an accurate SIRUCQTHE epidemiological model to get reliable predictions on the pandemic dynamics. Differently from the related literature, in the fitting phase, we make use of the google mobility reports to identify and predict the evolution of the infection rate. The effectiveness of the presented method is tested on the network of Italian regions. First, we describe the Italian epidemiological scenario in the COVID-19 second wave of contagions, showing the raw data available for the Italian scenario and discussing the main assumptions on the system parameters. Then, we present the different steps of the procedure used for the dynamical fitting of the SIRUCQTHE model. Finally, we compare the estimation results with the real data on the COVID-19 secondary waves in Italy. Provided the availability of reliable data to calibrate the model in heterogeneous scenarios, the proposed approach can be easily extended to cope with other scenarios. © 2021 IEEE.},
  author_keywords = {COVID-19; Dynamical fitting; Estimation; Identification; Pandemic modeling},
  keywords = {Forecasting; Disease transmission; Epidemiological modeling; Estimation results; Infection rates; Italian regions; Mitigation strategy; Predicting and analyzing; Scenario-based simulations; Shear waves},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Dotoli, M., Giarr, L. & Franco, E. (2021) Preface – Welcome to MED 2021 IN 2021 29th Mediterranean Conference on Control and Automation, MED 2021., 3 – 5. doi:10.1109/MED51440.2021.9495997
  [BibTeX] [Download PDF]

  @CONFERENCE{Dotoli20213,
  author = {Dotoli, Mariagrazia and Giarr, Laura and Franco, Elisa},
  title = {Preface - Welcome to MED 2021},
  year = {2021},
  journal = {2021 29th Mediterranean Conference on Control and Automation, MED 2021},
  pages = {3 – 5},
  doi = {10.1109/MED51440.2021.9495997},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113704740&doi=10.1109%2fMED51440.2021.9495997&partnerID=40&md5=ed125904693b2b05aaf44b9f9672c473},
  type = {Editorial},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Bronze Open Access}
  }

• Scarabaggio, P., Carli, R., Cavone, G., Epicoco, N. & Dotoli, M. (2021) Modeling, Estimation, and Optimal Control of Anti-COVID-19 Multi-dose Vaccine Administration IN IEEE International Conference on Automation Science and Engineering., 990 – 995. doi:10.1109/CASE49439.2021.9551418
  [BibTeX] [Abstract] [Download PDF]

  The recent trends of the COVID-19 research are being devoted to disease transmission modeling in presence of vaccinated individuals, while the emerging needs are being focused on developing effective strategies for the optimal distribution of vaccine between population. In this context, we propose a novel non-linear time-varying model that effectively supports policy-makers in predicting and analyzing the dynamics of COVID-19 when partially and fully immune individuals are included in the population. Differently from the related literature, where the common strategies typically rely on the prioritization of the different classes of individuals, we propose a novel Model Predictive Control approach to optimally control the multi-dose vaccine administration in the case the available number of doses is not sufficient to cover the whole population. Focusing on the minimization of the expected number of deaths, the approach discriminates between the number of first and second doses. We calibrate the model on the Israeli scenario using real data and we estimate the impact of the vaccine administration on the virus dynamics. Lastly, we assess the impact of the first dose of the Pfizer’s vaccine confirming the results of clinical tests. © 2021 IEEE.

  @CONFERENCE{Scarabaggio2021990,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Cavone, Graziana and Epicoco, Nicola and Dotoli, Mariagrazia},
  title = {Modeling, Estimation, and Optimal Control of Anti-COVID-19 Multi-dose Vaccine Administration},
  year = {2021},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2021-August},
  pages = {990 – 995},
  doi = {10.1109/CASE49439.2021.9551418},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117035432&doi=10.1109%2fCASE49439.2021.9551418&partnerID=40&md5=489bcdcd710fb127ad522dbebe163265},
  abstract = {The recent trends of the COVID-19 research are being devoted to disease transmission modeling in presence of vaccinated individuals, while the emerging needs are being focused on developing effective strategies for the optimal distribution of vaccine between population. In this context, we propose a novel non-linear time-varying model that effectively supports policy-makers in predicting and analyzing the dynamics of COVID-19 when partially and fully immune individuals are included in the population. Differently from the related literature, where the common strategies typically rely on the prioritization of the different classes of individuals, we propose a novel Model Predictive Control approach to optimally control the multi-dose vaccine administration in the case the available number of doses is not sufficient to cover the whole population. Focusing on the minimization of the expected number of deaths, the approach discriminates between the number of first and second doses. We calibrate the model on the Israeli scenario using real data and we estimate the impact of the vaccine administration on the virus dynamics. Lastly, we assess the impact of the first dose of the Pfizer's vaccine confirming the results of clinical tests. © 2021 IEEE.},
  author_keywords = {COVID-19; model predictive control; pandemic modeling; vaccine; vaccine distribution},
  keywords = {Model predictive control; Viruses; COVID-19; Disease transmission; Estimation controls; Model estimation; Model-predictive control; Modelling controls; Optimal controls; Pandemic modeling; Recent trends; Vaccine distributions; Vaccines},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 7; All Open Access, Bronze Open Access, Green Open Access}
  }

• Helmi, A. M., Carli, R., Dotoli, M. & Ramadan, H. S. (2021) Harris hawks optimization for the efficient reconfiguration of distribution networks IN 2021 29th Mediterranean Conference on Control and Automation, MED 2021., 214 – 219. doi:10.1109/MED51440.2021.9480179
  [BibTeX] [Abstract] [Download PDF]

  Improving the efficiency of distribution networks (DNs) is nowadays a challenging objective for modern power grids equipped with distributed generation and storage. In this context, the so-called network reconfiguration problem can be solved to obtain the optimal DN topology that minimizes the total power losses, while ensuring the voltage profile enhancement. The DN reconfiguration problem has NP-hard complexity; hence, finding near-optimal solutions in reasonable time is still an open research need. Facing this issue, this paper proposes a novel metaheuristic approach, where the recent Harris Hawks optimization algorithm is used to efficiently obtain near-optimal configurations. The effectiveness of the proposed method is validated through numerical experiments on the IEEE 85-bus system, comparing the achieved performance with the results obtained by other related techniques. © 2021 IEEE.

  @CONFERENCE{Helmi2021214,
  author = {Helmi, Ahmed M. and Carli, Raffaele and Dotoli, Mariagrazia and Ramadan, Haitham S.},
  title = {Harris hawks optimization for the efficient reconfiguration of distribution networks},
  year = {2021},
  journal = {2021 29th Mediterranean Conference on Control and Automation, MED 2021},
  pages = {214 – 219},
  doi = {10.1109/MED51440.2021.9480179},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113690851&doi=10.1109%2fMED51440.2021.9480179&partnerID=40&md5=ae29f6caf996f43c23ab7874ded72442},
  abstract = {Improving the efficiency of distribution networks (DNs) is nowadays a challenging objective for modern power grids equipped with distributed generation and storage. In this context, the so-called network reconfiguration problem can be solved to obtain the optimal DN topology that minimizes the total power losses, while ensuring the voltage profile enhancement. The DN reconfiguration problem has NP-hard complexity; hence, finding near-optimal solutions in reasonable time is still an open research need. Facing this issue, this paper proposes a novel metaheuristic approach, where the recent Harris Hawks optimization algorithm is used to efficiently obtain near-optimal configurations. The effectiveness of the proposed method is validated through numerical experiments on the IEEE 85-bus system, comparing the achieved performance with the results obtained by other related techniques. © 2021 IEEE.},
  author_keywords = {Distribution Network Reconfiguration; Harris Hawks Optimization; Metaheuristic Optimization; Microgrids},
  keywords = {Electric power transmission networks; NP-hard; Numerical methods; Distributed generation and storage; Meta-heuristic approach; Near-optimal solutions; Network re-configuration; Optimization algorithms; Reconfiguration of distribution networks; Reconfiguration problems; Voltage profile enhancements; Optimization},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Proia, S., Carli, R., Cavone, G. & Dotoli, M. (2021) A Literature Review on Control Techniques for Collaborative Robotics in Industrial Applications IN IEEE International Conference on Automation Science and Engineering., 591 – 596. doi:10.1109/CASE49439.2021.9551600
  [BibTeX] [Abstract] [Download PDF]

  One of the key enabling technologies that has made Industry 4.0 a concrete reality is without doubt collaborative robotics, which is also evolving as a fundamental pillar of the next revolution, the so-called Industry 5.0. The improvement of safety and employees’ well-being, together with the increment of profitability and productivity, are indeed the main goals of human-robot collaboration (HRC) in the industrial setting. The robotic controller design and the analysis of existing decision and control techniques are crucially needed to develop innovative models and state-of-the-art methodologies for a safe, ergonomic, and efficient HRC. To this aim, this article presents an accurate review of the most recent and relevant papers in the related field, focusing on the control perspective. All the surveyed works are carefully selected and categorized by target (i.e., safety, ergonomics, and efficiency), and then by problem and type of control, in presence or absence of optimization. Finally, the discussion of the achieved results and the analysis of the emerging challenges in this research field are reported, highlighting the identified gaps and promising future developments in the context of the digital evolution. © 2021 IEEE.

  @CONFERENCE{Proia2021591,
  author = {Proia, Silvia and Carli, Raffaele and Cavone, Graziana and Dotoli, Mariagrazia},
  title = {A Literature Review on Control Techniques for Collaborative Robotics in Industrial Applications},
  year = {2021},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2021-August},
  pages = {591 – 596},
  doi = {10.1109/CASE49439.2021.9551600},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116978273&doi=10.1109%2fCASE49439.2021.9551600&partnerID=40&md5=a834d330c2d2bedcecdff62c8eaceae7},
  abstract = {One of the key enabling technologies that has made Industry 4.0 a concrete reality is without doubt collaborative robotics, which is also evolving as a fundamental pillar of the next revolution, the so-called Industry 5.0. The improvement of safety and employees' well-being, together with the increment of profitability and productivity, are indeed the main goals of human-robot collaboration (HRC) in the industrial setting. The robotic controller design and the analysis of existing decision and control techniques are crucially needed to develop innovative models and state-of-the-art methodologies for a safe, ergonomic, and efficient HRC. To this aim, this article presents an accurate review of the most recent and relevant papers in the related field, focusing on the control perspective. All the surveyed works are carefully selected and categorized by target (i.e., safety, ergonomics, and efficiency), and then by problem and type of control, in presence or absence of optimization. Finally, the discussion of the achieved results and the analysis of the emerging challenges in this research field are reported, highlighting the identified gaps and promising future developments in the context of the digital evolution. © 2021 IEEE.},
  keywords = {Accident prevention; Controllers; Ergonomics; Industry 4.0; Robotics; Control techniques; Controller designs; Enabling technologies; Human-robot collaboration; Industrial settings; Innovative models; Literature reviews; Robotic controllers; State of the art; Well being; Collaborative robots},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 14}
  }

2020

• Carli, R., Dotoli, M., Jantzen, J., Kristensen, M. & Ben Othman, S. (2020) Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Samsø. IN Energy, 198.. doi:10.1016/j.energy.2020.117188
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on the Model Predictive Control (MPC) based energy scheduling of a smart microgrid equipped with non-controllable (i.e., with fixed power profile) and controllable (i.e., with flexible and programmable operation) electrical appliances, as well as photovoltaic (PV) panels, and a battery energy storage system (BESS). The proposed control strategy aims at a simultaneous optimal planning of the controllable loads, the shared resources (i.e., the storage system charge/discharge and renewable energy usage), and the energy exchange with the grid. The control scheme relies on an iterative finite horizon on-line optimization, implementing a mixed integer linear programming energy scheduling algorithm to maximize the self-supply with solar energy and/or minimize the daily cost of energy bought from the grid under time-varying energy pricing. At each time step, the resulting optimization problem is solved providing the optimal operations of controllable loads, the optimal amount of energy to be bought/sold from/to the grid, and the optimal charging/discharging profile for the BESS. The proposed energy scheduling approach is applied to the demand side management control of the marina of Ballen, Samsø (Denmark), where a smart microgrid is currently being implemented as a demonstrator in the Horizon2020 European research project SMILE. Simulations considering the marina electric consumption (340 boat sockets, a service building equipped with a sauna and a wastewater pumping station, and the harbour master’s office equipped with a heat pump), PV production (60kWp), and the BESS (237 kWh capacity) based on a public real dataset are carried out on a one year time series with a 1 h resolution. Simulations indicate that the proposed approach allows 90% exploitation of the production of the PV plant. Furthermore, results are compared to a naïve control approach. The MPC based energy scheduling improves the self-supply by 1.6% compared to the naïve control. Optimization of the business economy using the MPC approach, instead, yields to 8.2% savings in the yearly energy cost with respect to the naïve approach. © 2020 Elsevier Ltd

  @ARTICLE{Carli2020,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Jantzen, Jan and Kristensen, Michael and Ben Othman, Sarah},
  title = {Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Samsø},
  year = {2020},
  journal = {Energy},
  volume = {198},
  doi = {10.1016/j.energy.2020.117188},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082001819&doi=10.1016%2fj.energy.2020.117188&partnerID=40&md5=6477046a8e48af719b8ab95085e45579},
  abstract = {This paper focuses on the Model Predictive Control (MPC) based energy scheduling of a smart microgrid equipped with non-controllable (i.e., with fixed power profile) and controllable (i.e., with flexible and programmable operation) electrical appliances, as well as photovoltaic (PV) panels, and a battery energy storage system (BESS). The proposed control strategy aims at a simultaneous optimal planning of the controllable loads, the shared resources (i.e., the storage system charge/discharge and renewable energy usage), and the energy exchange with the grid. The control scheme relies on an iterative finite horizon on-line optimization, implementing a mixed integer linear programming energy scheduling algorithm to maximize the self-supply with solar energy and/or minimize the daily cost of energy bought from the grid under time-varying energy pricing. At each time step, the resulting optimization problem is solved providing the optimal operations of controllable loads, the optimal amount of energy to be bought/sold from/to the grid, and the optimal charging/discharging profile for the BESS. The proposed energy scheduling approach is applied to the demand side management control of the marina of Ballen, Samsø (Denmark), where a smart microgrid is currently being implemented as a demonstrator in the Horizon2020 European research project SMILE. Simulations considering the marina electric consumption (340 boat sockets, a service building equipped with a sauna and a wastewater pumping station, and the harbour master's office equipped with a heat pump), PV production (60kWp), and the BESS (237 kWh capacity) based on a public real dataset are carried out on a one year time series with a 1 h resolution. Simulations indicate that the proposed approach allows 90% exploitation of the production of the PV plant. Furthermore, results are compared to a naïve control approach. The MPC based energy scheduling improves the self-supply by 1.6% compared to the naïve control. Optimization of the business economy using the MPC approach, instead, yields to 8.2% savings in the yearly energy cost with respect to the naïve approach. © 2020 Elsevier Ltd},
  author_keywords = {Demand side management; Energy management; Energy storage; Microgrid; Model predictive control; On-line scheduling; Optimization algorithm; Renewable energy},
  keywords = {Denmark; Costs; Demand side management; Economics; Electric utilities; Energy management; Energy storage; Energy utilization; Integer programming; Iterative methods; Marinas; Microgrids; Model predictive control; Photovoltaic cells; Predictive control systems; Pumping plants; Scheduling; Scheduling algorithms; Solar energy; Battery energy storage systems; European research project; Micro grid; Mixed integer linear programming; Online scheduling; Optimization algorithms; Renewable energies; Wastewater pumping station; alternative energy; demand-side management; energy storage; exploitation; linear programing; optimization; photovoltaic system; pumping; smart grid; time series; wastewater; Electric power system control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 79; All Open Access, Green Open Access}
  }

• Carli, R. & Dotoli, M. (2020) A dynamic programming approach for the decentralized control of discrete optimizers with quadratic utilities and shared constraint IN 2020 28th Mediterranean Conference on Control and Automation, MED 2020., 611 – 616. doi:10.1109/MED48518.2020.9183012
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses the problem of controlling a large set of agents, each with a quadratic utility function depending on individual combinatorial choices, and all sharing an affine constraint on available resources. Such a problem is formulated as an integer mono-constrained bounded quadratic knapsack problem. Differently from the centralized approaches typically proposed in the related literature, we present a new decentralized algorithm to solve the problem approximately in polynomial time by decomposing it into a finite series of sub-problems. We assume a minimal communication structure through the presence of a central coordinator that ensures the information exchange between agents. The proposed solution relies on a decentralized control algorithm that combines discrete dynamic programming with additive decomposition and value functions approximation. The optimality and complexity of the presented strategy are discussed, highlighting that the algorithm constitutes a fully polynomial approximation scheme. Numerical experiments are presented to show the effectiveness of the approach in the optimal resolution of large-scale instances. © 2020 IEEE.

  @CONFERENCE{Carli2020611,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A dynamic programming approach for the decentralized control of discrete optimizers with quadratic utilities and shared constraint},
  year = {2020},
  journal = {2020 28th Mediterranean Conference on Control and Automation, MED 2020},
  pages = {611 – 616},
  doi = {10.1109/MED48518.2020.9183012},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092158668&doi=10.1109%2fMED48518.2020.9183012&partnerID=40&md5=e3c2836d54651610b499a9686ac98fe7},
  abstract = {This paper addresses the problem of controlling a large set of agents, each with a quadratic utility function depending on individual combinatorial choices, and all sharing an affine constraint on available resources. Such a problem is formulated as an integer mono-constrained bounded quadratic knapsack problem. Differently from the centralized approaches typically proposed in the related literature, we present a new decentralized algorithm to solve the problem approximately in polynomial time by decomposing it into a finite series of sub-problems. We assume a minimal communication structure through the presence of a central coordinator that ensures the information exchange between agents. The proposed solution relies on a decentralized control algorithm that combines discrete dynamic programming with additive decomposition and value functions approximation. The optimality and complexity of the presented strategy are discussed, highlighting that the algorithm constitutes a fully polynomial approximation scheme. Numerical experiments are presented to show the effectiveness of the approach in the optimal resolution of large-scale instances. © 2020 IEEE.},
  author_keywords = {Decentralized optimization; Dynamic programming; Fully polynomial-time approximation scheme; Knapsack problem},
  keywords = {Approximation algorithms; Combinatorial optimization; Dynamic programming; Polynomial approximation; Additive decomposition; Centralized approaches; Communication structures; Decentralized algorithms; Information exchanges; Numerical experiments; Optimal resolution; Quadratic knapsack problems; Decentralized control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Scarabaggio, P., Carli, R. & Dotoli, M. (2020) A fast and effective algorithm for influence maximization in large-scale independent cascade networks IN 7th International Conference on Control, Decision and Information Technologies, CoDIT 2020., 639 – 644. doi:10.1109/CoDIT49905.2020.9263914
  [BibTeX] [Abstract] [Download PDF]

  A characteristic of social networks is the ability to quickly spread information between a large group of people. The widespread use of online social networks (e.g., Facebook) increases the interest of researchers on how influence propagates through these networks. One of the most important research issues in this field is the so-called influence maximization problem, which essentially consists in selecting the most influential users (i.e., those who are able to maximize the spread of influence through the social network). Due to its practical importance in various applications (e.g., viral marketing), such a problem has been studied in several variants. Nevertheless, the current open challenge in the resolution of the influence maximization problem still concerns achieving a good trade-off between accuracy and computational time. In this context, based on independent cascade modeling of social networks, we propose a novel low-complexity and highly accurate algorithm for selecting an initial group of nodes to maximize the spread of influence in large-scale networks. In particular, the key idea consists in iteratively removing the overlap of influence spread induced by different seed nodes. The application to several numerical experiments based on real datasets proves that the proposed algorithm effectively finds practical near-optimal solutions of the addressed influence maximization problem in a computationally efficient fashion. Finally, the comparison with the state of the art algorithms demonstrates that in large scale scenarios the proposed approach shows higher performance in terms of influence spread and running time. © 2020 IEEE.

  @CONFERENCE{Scarabaggio2020639,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A fast and effective algorithm for influence maximization in large-scale independent cascade networks},
  year = {2020},
  journal = {7th International Conference on Control, Decision and Information Technologies, CoDIT 2020},
  pages = {639 – 644},
  doi = {10.1109/CoDIT49905.2020.9263914},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098236199&doi=10.1109%2fCoDIT49905.2020.9263914&partnerID=40&md5=003f7d44f921ecd0bf436dacb2d3e136},
  abstract = {A characteristic of social networks is the ability to quickly spread information between a large group of people. The widespread use of online social networks (e.g., Facebook) increases the interest of researchers on how influence propagates through these networks. One of the most important research issues in this field is the so-called influence maximization problem, which essentially consists in selecting the most influential users (i.e., those who are able to maximize the spread of influence through the social network). Due to its practical importance in various applications (e.g., viral marketing), such a problem has been studied in several variants. Nevertheless, the current open challenge in the resolution of the influence maximization problem still concerns achieving a good trade-off between accuracy and computational time. In this context, based on independent cascade modeling of social networks, we propose a novel low-complexity and highly accurate algorithm for selecting an initial group of nodes to maximize the spread of influence in large-scale networks. In particular, the key idea consists in iteratively removing the overlap of influence spread induced by different seed nodes. The application to several numerical experiments based on real datasets proves that the proposed algorithm effectively finds practical near-optimal solutions of the addressed influence maximization problem in a computationally efficient fashion. Finally, the comparison with the state of the art algorithms demonstrates that in large scale scenarios the proposed approach shows higher performance in terms of influence spread and running time. © 2020 IEEE.},
  keywords = {Economic and social effects; Iterative methods; Computationally efficient; Influence maximizations; Most influential users; Near-optimal solutions; Numerical experiments; On-line social networks; Practical importance; State-of-the-art algorithms; Social networking (online)},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Carli, R., Cavone, G., Pippia, T., Schutter, B. D. & Dotoli, M. (2020) A Robust MPC Energy Scheduling Strategy for Multi-Carrier Microgrids IN IEEE International Conference on Automation Science and Engineering., 152 – 158. doi:10.1109/CASE48305.2020.9216875
  [BibTeX] [Abstract] [Download PDF]

  We present a Robust Model Predictive Control (RMPC) approach for multi-carrier microgrids, i.e., microgrids based on gas and electricity. The microgrid that we consider includes thermal loads, electrical loads, renewable energy sources, energy storage systems, heat pumps, and combined heat and power plants. Moreover, the system under control is affected by several external disturbances, e.g., uncertainty in renewable energy generation, electrical and thermal demand. The goal of the controller is to minimize the overall economical cost and the energy exchange with the main grid, while guaranteeing comfort. Whereas several RMPC methods have been developed for electrical or thermal microgrids, little or no attention has been devoted to robust control of multi-carrier microgrids. Therefore, we consider a novel RMPC algorithm that can improve the performance with respect to classical deterministic Model Predictive Control (Det-MPC) controllers in the context of multi-carrier microgrids. The RMPC method relies on the box-uncertainty-set robust optimization, where uncertain parameters are assumed to take their values from different intervals independently. The RMPC approach is able to successfully satisfy the constraints even in the presence of the mentioned disturbances. Simulations of a realistic residential case study show the benefits of the proposed approach with respect to Det-MPC controllers. © 2020 IEEE.

  @CONFERENCE{Carli2020152,
  author = {Carli, Raffaele and Cavone, Graziana and Pippia, Tomas and Schutter, Bart De and Dotoli, Mariagrazia},
  title = {A Robust MPC Energy Scheduling Strategy for Multi-Carrier Microgrids},
  year = {2020},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2020-August},
  pages = {152 – 158},
  doi = {10.1109/CASE48305.2020.9216875},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094114652&doi=10.1109%2fCASE48305.2020.9216875&partnerID=40&md5=92ef257518791ef22242636d1c989285},
  abstract = {We present a Robust Model Predictive Control (RMPC) approach for multi-carrier microgrids, i.e., microgrids based on gas and electricity. The microgrid that we consider includes thermal loads, electrical loads, renewable energy sources, energy storage systems, heat pumps, and combined heat and power plants. Moreover, the system under control is affected by several external disturbances, e.g., uncertainty in renewable energy generation, electrical and thermal demand. The goal of the controller is to minimize the overall economical cost and the energy exchange with the main grid, while guaranteeing comfort. Whereas several RMPC methods have been developed for electrical or thermal microgrids, little or no attention has been devoted to robust control of multi-carrier microgrids. Therefore, we consider a novel RMPC algorithm that can improve the performance with respect to classical deterministic Model Predictive Control (Det-MPC) controllers in the context of multi-carrier microgrids. The RMPC method relies on the box-uncertainty-set robust optimization, where uncertain parameters are assumed to take their values from different intervals independently. The RMPC approach is able to successfully satisfy the constraints even in the presence of the mentioned disturbances. Simulations of a realistic residential case study show the benefits of the proposed approach with respect to Det-MPC controllers. © 2020 IEEE.},
  author_keywords = {Energy and Environment-Aware Automation; Microgrid; Optimization and Optimal Control; Robust Model Predictive Control; Set-based Uncertainty},
  keywords = {Cogeneration plants; Electric energy storage; Electric loads; Microgrids; Model predictive control; Optimization; Predictive control systems; Renewable energy resources; Robust control; Uncertainty analysis; Deterministic modeling; Energy storage systems; External disturbances; Renewable energy generation; Renewable energy source; Robust model predictive controls (RMPC); Scheduling strategies; Uncertain parameters; Controllers},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 16}
  }

• Carli, R., Cavone, G., Epicoco, N., Scarabaggio, P. & Dotoli, M. (2020) Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario. IN Annual Reviews in Control, 50.373 – 393. doi:10.1016/j.arcontrol.2020.09.005
  [BibTeX] [Abstract] [Download PDF]

  The COVID-19 outbreak is deeply influencing the global social and economic framework, due to restrictive measures adopted worldwide by governments to counteract the pandemic contagion. In multi-region areas such as Italy, where the contagion peak has been reached, it is crucial to find targeted and coordinated optimal exit and restarting strategies on a regional basis to effectively cope with possible onset of further epidemic waves, while efficiently returning the economic activities to their standard level of intensity. Differently from the related literature, where modeling and controlling the pandemic contagion is typically addressed on a national basis, this paper proposes an optimal control approach that supports governments in defining the most effective strategies to be adopted during post-lockdown mitigation phases in a multi-region scenario. Based on the joint use of a non-linear Model Predictive Control scheme and a modified Susceptible-Infected-Recovered (SIR)-based epidemiological model, the approach is aimed at minimizing the cost of the so-called non-pharmaceutical interventions (that is, mitigation strategies), while ensuring that the capacity of the network of regional healthcare systems is not violated. In addition, the proposed approach supports policy makers in taking targeted intervention decisions on different regions by an integrated and structured model, thus both respecting the specific regional health systems characteristics and improving the system-wide performance by avoiding uncoordinated actions of the regions. The methodology is tested on the COVID-19 outbreak data related to the network of Italian regions, showing its effectiveness in properly supporting the definition of effective regional strategies for managing the COVID-19 diffusion. © 2020 Elsevier Ltd

  @ARTICLE{Carli2020373,
  author = {Carli, Raffaele and Cavone, Graziana and Epicoco, Nicola and Scarabaggio, Paolo and Dotoli, Mariagrazia},
  title = {Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario},
  year = {2020},
  journal = {Annual Reviews in Control},
  volume = {50},
  pages = {373 – 393},
  doi = {10.1016/j.arcontrol.2020.09.005},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097753585&doi=10.1016%2fj.arcontrol.2020.09.005&partnerID=40&md5=adce49e71a999948867e93de3ae2e142},
  abstract = {The COVID-19 outbreak is deeply influencing the global social and economic framework, due to restrictive measures adopted worldwide by governments to counteract the pandemic contagion. In multi-region areas such as Italy, where the contagion peak has been reached, it is crucial to find targeted and coordinated optimal exit and restarting strategies on a regional basis to effectively cope with possible onset of further epidemic waves, while efficiently returning the economic activities to their standard level of intensity. Differently from the related literature, where modeling and controlling the pandemic contagion is typically addressed on a national basis, this paper proposes an optimal control approach that supports governments in defining the most effective strategies to be adopted during post-lockdown mitigation phases in a multi-region scenario. Based on the joint use of a non-linear Model Predictive Control scheme and a modified Susceptible-Infected-Recovered (SIR)-based epidemiological model, the approach is aimed at minimizing the cost of the so-called non-pharmaceutical interventions (that is, mitigation strategies), while ensuring that the capacity of the network of regional healthcare systems is not violated. In addition, the proposed approach supports policy makers in taking targeted intervention decisions on different regions by an integrated and structured model, thus both respecting the specific regional health systems characteristics and improving the system-wide performance by avoiding uncoordinated actions of the regions. The methodology is tested on the COVID-19 outbreak data related to the network of Italian regions, showing its effectiveness in properly supporting the definition of effective regional strategies for managing the COVID-19 diffusion. © 2020 Elsevier Ltd},
  author_keywords = {COVID-19; Epidemic control; MPC; Multi-region SIR model; Pandemic modeling; Post-lockdown mitigation strategies; SIR model},
  keywords = {Economics; Economic activities; Economic framework; Epidemiological modeling; Health-care system; Mitigation strategy; Non-pharmaceutical interventions; Nonlinear model predictive control; Optimal controls; Model predictive control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 76; All Open Access, Green Open Access}
  }

• Cavone, G., Epicoco, N. & Dotoli, M. (2020) Process re-engineering based on colored petri nets: The case of an Italian textile company IN 2020 28th Mediterranean Conference on Control and Automation, MED 2020., 856 – 861. doi:10.1109/MED48518.2020.9182937
  [BibTeX] [Abstract] [Download PDF]

  Business process re-engineering is crucial for manufacturing companies to improve their productivity and efficiency. The identification of the main criticalities affecting the production processes and the implementation of effective re-engineering solutions can significantly reduce the company losses. However, such actions can be unsuccessful if suitable preliminary investigations on the effectiveness of the solutions are not performed. This paper proposes an integrated process re-engineering technique that allows to: identify workflows via the Unified Modeling Language; model and simulate the business process via Colored Petri Nets (CPNs); detect bottlenecks and waste sources through the Value Stream Mapping tool; rank the impact of the detected criticalities via a mathematical formulation of the Genba-Shikumi lean philosophy; simulate the re-engineering actions and evaluate their effectiveness using the CPN model. The aim is to offer an intuitive tool for strategic decision making, deployable at a managerial level in a digital twin approach. The proposed technique is tested on a textile company located in Southern Italy, showing its effectiveness in removing inefficiencies and ensuring the continuous improvement of the production process. © 2020 IEEE.

  @CONFERENCE{Cavone2020856,
  author = {Cavone, Graziana and Epicoco, Nicola and Dotoli, Mariagrazia},
  title = {Process re-engineering based on colored petri nets: The case of an Italian textile company},
  year = {2020},
  journal = {2020 28th Mediterranean Conference on Control and Automation, MED 2020},
  pages = {856 – 861},
  doi = {10.1109/MED48518.2020.9182937},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092143469&doi=10.1109%2fMED48518.2020.9182937&partnerID=40&md5=8c365f0bdb732312eac56e75db5e46d8},
  abstract = {Business process re-engineering is crucial for manufacturing companies to improve their productivity and efficiency. The identification of the main criticalities affecting the production processes and the implementation of effective re-engineering solutions can significantly reduce the company losses. However, such actions can be unsuccessful if suitable preliminary investigations on the effectiveness of the solutions are not performed. This paper proposes an integrated process re-engineering technique that allows to: identify workflows via the Unified Modeling Language; model and simulate the business process via Colored Petri Nets (CPNs); detect bottlenecks and waste sources through the Value Stream Mapping tool; rank the impact of the detected criticalities via a mathematical formulation of the Genba-Shikumi lean philosophy; simulate the re-engineering actions and evaluate their effectiveness using the CPN model. The aim is to offer an intuitive tool for strategic decision making, deployable at a managerial level in a digital twin approach. The proposed technique is tested on a textile company located in Southern Italy, showing its effectiveness in removing inefficiencies and ensuring the continuous improvement of the production process. © 2020 IEEE.},
  author_keywords = {Colored Petri Nets; Genba-Shikumi; Manufacturing; Process Re-engineering; Unified Modeling Language},
  keywords = {Computer hardware description languages; Criticality (nuclear fission); Decision making; Digital twin; Reengineering; Textiles; Unified Modeling Language; Business process re-engineering; Colored Petri Nets; Continuous improvements; Manufacturing companies; Mathematical formulation; Process reengineering; Strategic decision making; Value stream mapping; Petri nets},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 4}
  }

• Scarabaggio, P., Carli, R., Cavone, G. & Dotoli, M. (2020) Smart control strategies for primary frequency regulation through electric vehicles: A battery degradation perspective. IN Energies, 13.. doi:10.3390/en13174586
  [BibTeX] [Abstract] [Download PDF]

  Nowadays, due to the decreasing use of traditional generators in favor of renewable energy sources, power grids are facing a reduction of system inertia and primary frequency regulation capability. Such an issue is exacerbated by the continuously increasing number of electric vehicles (EVs), which results in enforcing novel approaches in the grid operations management. However, from being an issue, the increase of EVs may turn to be a solution to several power system challenges. In this context, a crucial role is played by the so-called vehicle-to-grid (V2G) mode of operation, which has the potential to provide ancillary services to the power grid, such as peak clipping, load shifting, and frequency regulation. More in detail, EVs have recently started to be effectively used for one of the most traditional frequency regulation approaches: the so-called frequency droop control (FDC). This is a primary frequency regulation, currently obtained by adjusting the active power of generators in the main grid. Because to the decommissioning of traditional power plants, EVs are thus recognized as particularly valuable solutions since they can respond to frequency deviation signals by charging or discharging their batteries. Against this background, we address frequency regulation of a power grid model including loads, traditional generators, and several EVs. The latter independently participate in the grid optimization process providing the grid with ancillary services, namely the FDC. We propose two novel control strategies for the optimal control of the batteries of EVs during the frequency regulation service. On the one hand, the control strategies ensure re-balancing the power and stabilizing the frequency of the main grid. On the other hand, the approaches are able to satisfy different types of needs of EVs during the charging process. Differently from the related literature, where the EVs perspective is generally oriented to achieve the optimal charge level, the proposed approaches aim at minimizing the degradation of battery devices. Finally, the proposed strategies are compared with other state-of-the-art V2G control approaches. The results of numerical experiments using a realistic power grid model show the effectiveness of the proposed strategies under the actual operating conditions. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

  @ARTICLE{Scarabaggio2020,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Cavone, Graziana and Dotoli, Mariagrazia},
  title = {Smart control strategies for primary frequency regulation through electric vehicles: A battery degradation perspective},
  year = {2020},
  journal = {Energies},
  volume = {13},
  number = {17},
  doi = {10.3390/en13174586},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090919511&doi=10.3390%2fen13174586&partnerID=40&md5=d7f07f0a819d149b5f1c143b707e731d},
  abstract = {Nowadays, due to the decreasing use of traditional generators in favor of renewable energy sources, power grids are facing a reduction of system inertia and primary frequency regulation capability. Such an issue is exacerbated by the continuously increasing number of electric vehicles (EVs), which results in enforcing novel approaches in the grid operations management. However, from being an issue, the increase of EVs may turn to be a solution to several power system challenges. In this context, a crucial role is played by the so-called vehicle-to-grid (V2G) mode of operation, which has the potential to provide ancillary services to the power grid, such as peak clipping, load shifting, and frequency regulation. More in detail, EVs have recently started to be effectively used for one of the most traditional frequency regulation approaches: the so-called frequency droop control (FDC). This is a primary frequency regulation, currently obtained by adjusting the active power of generators in the main grid. Because to the decommissioning of traditional power plants, EVs are thus recognized as particularly valuable solutions since they can respond to frequency deviation signals by charging or discharging their batteries. Against this background, we address frequency regulation of a power grid model including loads, traditional generators, and several EVs. The latter independently participate in the grid optimization process providing the grid with ancillary services, namely the FDC. We propose two novel control strategies for the optimal control of the batteries of EVs during the frequency regulation service. On the one hand, the control strategies ensure re-balancing the power and stabilizing the frequency of the main grid. On the other hand, the approaches are able to satisfy different types of needs of EVs during the charging process. Differently from the related literature, where the EVs perspective is generally oriented to achieve the optimal charge level, the proposed approaches aim at minimizing the degradation of battery devices. Finally, the proposed strategies are compared with other state-of-the-art V2G control approaches. The results of numerical experiments using a realistic power grid model show the effectiveness of the proposed strategies under the actual operating conditions. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).},
  author_keywords = {Electric vehicle batteries (EVBs); Electric vehicles (EVs); Frequency droop control (FDC); Vehicle-to-grid (V2G)},
  keywords = {Automotive batteries; Charging (batteries); Electric control equipment; Electric generators; Electric network topology; Electric power transmission networks; Electric vehicles; Microgrids; Renewable energy resources; Vehicle-to-grid; Electric Vehicles (EVs); Frequency regulation services; Frequency regulations; Numerical experiments; Primary frequency regulation; Renewable energy source; Smart control strategies; Vehicle to Grid (V2G); Electric power system control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 37; All Open Access, Gold Open Access, Green Open Access}
  }

• Dotoli, M., Telmoudi, A. J., Toloo, M. & Viedma, E. H. (2020) Welcome IN 7th International Conference on Control, Decision and Information Technologies, CoDIT 2020.. doi:10.1109/CoDIT49905.2020.9263895
  [BibTeX] [Download PDF]

  @CONFERENCE{Dotoli2020,
  author = {Dotoli, Mariagrazia and Telmoudi, Achraf Jabeur and Toloo, Mehdi and Viedma, Enrique H.},
  title = {Welcome},
  year = {2020},
  journal = {7th International Conference on Control, Decision and Information Technologies, CoDIT 2020},
  doi = {10.1109/CoDIT49905.2020.9263895},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098237456&doi=10.1109%2fCoDIT49905.2020.9263895&partnerID=40&md5=630582e542b3b8e1e19d72249c100123},
  type = {Editorial},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Bronze Open Access}
  }

• Cavone, G., Montaruli, V., Van Den Boom, T. J. J. & Dotoli, M. (2020) Demand-Oriented Rescheduling of Railway Traffic in Case of Delays IN 7th International Conference on Control, Decision and Information Technologies, CoDIT 2020., 1040 – 1045. doi:10.1109/CoDIT49905.2020.9263874
  [BibTeX] [Abstract] [Download PDF]

  The railway sector is currently experiencing a rapid evolution from fully manual towards automatic rail traffic control systems, due to the growth of transport demand and networks complexity. One of the main issues is to automatically and effectively reschedule the railway traffic in case of unexpected events, thus avoiding dramatic drops in the system performance. In the literature, the majority of contributions aims at automatically minimizing the train delays or optimizing the railway system performance (e.g., energy consumption). However, such strategies are not always able to ensure satisfaction of passengers that in many cases experience the side-effects of the rescheduling actions (e.g., cancellation of train runs, cancellation of coincidences, rerouting of trains, etc.). In this paper, we propose a demandoriented train rescheduling automatic technique that minimizes simultaneously the train delays and the discomfort perceived by passengers. When an unexpected event occurs, the rescheduling problem is set, based on the current state and nominal timetable of the system and its passengers flows. Hence, the problem is solved providing the control actions necessary to minimize both the delays and number of passengers subject to severe side-effects. The rescheduling is here formulated as a mixed integer linear programming problem, where the operating rules of the railway network are represented by linear equality and inequality constraints, while the objective is a linear function to be minimized. The possible control actions consist in re-timing the rail traffic and modifying the connections among lines. The proposed technique is preliminarily evaluated on a test case and a discussion is provided on the outcomes. © 2020 IEEE.

  @CONFERENCE{Cavone20201040,
  author = {Cavone, Graziana and Montaruli, Virginia and Van Den Boom, Ton J.J. and Dotoli, Mariagrazia},
  title = {Demand-Oriented Rescheduling of Railway Traffic in Case of Delays},
  year = {2020},
  journal = {7th International Conference on Control, Decision and Information Technologies, CoDIT 2020},
  pages = {1040 – 1045},
  doi = {10.1109/CoDIT49905.2020.9263874},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098278130&doi=10.1109%2fCoDIT49905.2020.9263874&partnerID=40&md5=77e95b60271d0546bb0ca7e53e9fbfc4},
  abstract = {The railway sector is currently experiencing a rapid evolution from fully manual towards automatic rail traffic control systems, due to the growth of transport demand and networks complexity. One of the main issues is to automatically and effectively reschedule the railway traffic in case of unexpected events, thus avoiding dramatic drops in the system performance. In the literature, the majority of contributions aims at automatically minimizing the train delays or optimizing the railway system performance (e.g., energy consumption). However, such strategies are not always able to ensure satisfaction of passengers that in many cases experience the side-effects of the rescheduling actions (e.g., cancellation of train runs, cancellation of coincidences, rerouting of trains, etc.). In this paper, we propose a demandoriented train rescheduling automatic technique that minimizes simultaneously the train delays and the discomfort perceived by passengers. When an unexpected event occurs, the rescheduling problem is set, based on the current state and nominal timetable of the system and its passengers flows. Hence, the problem is solved providing the control actions necessary to minimize both the delays and number of passengers subject to severe side-effects. The rescheduling is here formulated as a mixed integer linear programming problem, where the operating rules of the railway network are represented by linear equality and inequality constraints, while the objective is a linear function to be minimized. The possible control actions consist in re-timing the rail traffic and modifying the connections among lines. The proposed technique is preliminarily evaluated on a test case and a discussion is provided on the outcomes. © 2020 IEEE.},
  author_keywords = {demand-oriented rescheduling; passengers satisfaction; Railways},
  keywords = {Constraint theory; Energy utilization; Integer programming; Railroad traffic control; Railroads; Rails; Automatic rail traffic control system; Automatic technique; Inequality constraint; Linear functions; Mixed integer linear programming problems; Rescheduling problem; Train rescheduling; Unexpected events; Railroad transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 4}
  }

• Carli, R., Digiesi, S., Dotoli, M. & Facchini, F. (2020) A control strategy for smart energy charging of warehouse material handling equipment IN Procedia Manufacturing., 503 – 510. doi:10.1016/j.promfg.2020.02.041
  [BibTeX] [Abstract] [Download PDF]

  The common driver of the ‘green-warehouse’ strategy is based on the reduction of energy consumption. In warehouses with ‘picker-to-part’ operations the minimization of energy due to material handling activities can be achieved by means of different policies: by adopting smart automatic picking systems, by adopting energy-efficient material handling equipment (MHE) as well as by identifying flexible layouts. In most cases, these strategies require investments characterized by high pay-back times. In this context, management strategies focused on the adoption of available equipment allow to increase the warehouse productivity at negligible costs. With this purpose, an optimization model is proposed in order to identify an optimal control strategy for the battery charging of a fleet of electric mobile MHE (e.g., forklifts), allowing minimizing the economic and environmental impact of material handling activities in labor-intensive warehouses. The resulting scheduling problem is formalized as an integer programming (IP) problem aimed at minimizing the total cost, which is the sum of the penalty cost related to makespan over all the material handling activities and the total electricity cost for charging batteries of MHE. Numerical experiments are used to investigate and quantify the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the International Conference on Industry 4.0 and Smart Manufacturing.

  @CONFERENCE{Carli2020503,
  author = {Carli, Raffaele and Digiesi, Salvatore and Dotoli, Mariagrazia and Facchini, Francesco},
  title = {A control strategy for smart energy charging of warehouse material handling equipment},
  year = {2020},
  journal = {Procedia Manufacturing},
  volume = {42},
  pages = {503 – 510},
  doi = {10.1016/j.promfg.2020.02.041},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084243764&doi=10.1016%2fj.promfg.2020.02.041&partnerID=40&md5=795bb61103f666156bed4ba693a6503f},
  abstract = {The common driver of the 'green-warehouse' strategy is based on the reduction of energy consumption. In warehouses with 'picker-to-part' operations the minimization of energy due to material handling activities can be achieved by means of different policies: by adopting smart automatic picking systems, by adopting energy-efficient material handling equipment (MHE) as well as by identifying flexible layouts. In most cases, these strategies require investments characterized by high pay-back times. In this context, management strategies focused on the adoption of available equipment allow to increase the warehouse productivity at negligible costs. With this purpose, an optimization model is proposed in order to identify an optimal control strategy for the battery charging of a fleet of electric mobile MHE (e.g., forklifts), allowing minimizing the economic and environmental impact of material handling activities in labor-intensive warehouses. The resulting scheduling problem is formalized as an integer programming (IP) problem aimed at minimizing the total cost, which is the sum of the penalty cost related to makespan over all the material handling activities and the total electricity cost for charging batteries of MHE. Numerical experiments are used to investigate and quantify the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the International Conference on Industry 4.0 and Smart Manufacturing.},
  author_keywords = {Battery smart charging; Green warehouse; Industrial/manufacturing demand side management; Integer programming; Material handling activity; Optimization; Warehouse energy management},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 17; All Open Access, Gold Open Access, Green Open Access}
  }

• Dotoli, M. & Epicoco, N. (2020) Integrated Network Design of Agile Resource-Efficient Supply Chains under Uncertainty. IN IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50.4530 – 4544. doi:10.1109/TSMC.2018.2854620
  [BibTeX] [Abstract] [Download PDF]

  We present a novel method for supply chain network (SCN) design under uncertainty that jointly solves the candidate selection, the order allocation, and the transportation mode selection problems. In the proposed method, four steps are executed in cascade. First, a cross-efficiency fuzzy data envelopment analysis technique ranks the candidates of each SCN stage in a multiobjective perspective and under uncertain data. Second, a fuzzy linear integer programming model determines the supplies required from each actor by those belonging to the subsequent SCN stage. This step determines the best compromise between candidates’ efficiencies, estimated costs, and delivery time, considering stock levels and uncertain capacity of actors, while satisfying customers’ uncertain demand. The third step evaluates the efficiency of the transportation alternatives under uncertain data to optimally plan the transport chain. Finally, the fourth step measures the performance of the designed SCN. The method provides as a result an integrated, agile, and resource-efficient design of the SCN under uncertainty. Its application to a case study shows it is effective in selecting the SCN partners, assigning the corresponding order quantities, and delivering them to customers. Validation is obtained by comparison with well-known approaches and statistical analysis. © 2018 IEEE.

  @ARTICLE{Dotoli20204530,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola},
  title = {Integrated Network Design of Agile Resource-Efficient Supply Chains under Uncertainty},
  year = {2020},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems},
  volume = {50},
  number = {11},
  pages = {4530 – 4544},
  doi = {10.1109/TSMC.2018.2854620},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050603527&doi=10.1109%2fTSMC.2018.2854620&partnerID=40&md5=7ca65828d2287dd518f0fe708d036197},
  abstract = {We present a novel method for supply chain network (SCN) design under uncertainty that jointly solves the candidate selection, the order allocation, and the transportation mode selection problems. In the proposed method, four steps are executed in cascade. First, a cross-efficiency fuzzy data envelopment analysis technique ranks the candidates of each SCN stage in a multiobjective perspective and under uncertain data. Second, a fuzzy linear integer programming model determines the supplies required from each actor by those belonging to the subsequent SCN stage. This step determines the best compromise between candidates' efficiencies, estimated costs, and delivery time, considering stock levels and uncertain capacity of actors, while satisfying customers' uncertain demand. The third step evaluates the efficiency of the transportation alternatives under uncertain data to optimally plan the transport chain. Finally, the fourth step measures the performance of the designed SCN. The method provides as a result an integrated, agile, and resource-efficient design of the SCN under uncertainty. Its application to a case study shows it is effective in selecting the SCN partners, assigning the corresponding order quantities, and delivering them to customers. Validation is obtained by comparison with well-known approaches and statistical analysis. © 2018 IEEE.},
  author_keywords = {Agility; data envelopment analysis (DEA); efficiency; fuzzy set theory; supply chain network (SCN) design},
  keywords = {Data envelopment analysis; Decision making; Decision theory; Efficiency; Fuzzy set theory; Integer programming; Linear programming; Random processes; Stochastic systems; Supply chains; Transportation; Uncertainty analysis; Agility; Candidate selection; Design under uncertainty; Fuzzy data envelopment analysis; Linear integer programming; Resource management; Supply chain network; Uncertainty; Information management},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 8}
  }

• Hosseini, S. M., Carli, R., Parisio, A. & Dotoli, M. (2020) Robust Decentralized Charge Control of Electric Vehicles under Uncertainty on Inelastic Demand and Energy Pricing IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 1834 – 1839. doi:10.1109/SMC42975.2020.9283440
  [BibTeX] [Abstract] [Download PDF]

  This paper proposes a novel robust decentralized charging strategy for large-scale EV fleets. The system incorporates multiple EVs as well as inelastic loads connected to the power grid under power flow limits. We aim at minimizing both the overall charging energy payment and the aggregated battery degradation cost of EVs while preserving the robustness of the solution against uncertainties in the price of the electricity purchased from the power grid and the demand of inelastic loads. The proposed approach relies on the so-called uncertainty set-based robust optimization. The resulting charge scheduling problem is formulated as a tractable quadratic programming problem where all the EVs’ decisions are coupled via the grid resource-sharing constraints and the robust counterpart supporting constraints. We adopt an extended Jacobi-Proximal Alternating Direction Method of Multipliers algorithm to solve effectively the formulated scheduling problem in a decentralized fashion, thus allowing the method applicability to large scale fleets. Simulations of a realistic case study show that the proposed approach not only reduces the costs of the EV fleet, but also maintains the robustness of the solution against perturbations in different uncertain parameters, which is beneficial for both EVs’ users and the power grid. © 2020 IEEE.

  @CONFERENCE{Hosseini20201834,
  author = {Hosseini, Seyed Mohsen and Carli, Raffaele and Parisio, Alessandra and Dotoli, Mariagrazia},
  title = {Robust Decentralized Charge Control of Electric Vehicles under Uncertainty on Inelastic Demand and Energy Pricing},
  year = {2020},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {2020-October},
  pages = {1834 – 1839},
  doi = {10.1109/SMC42975.2020.9283440},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098877625&doi=10.1109%2fSMC42975.2020.9283440&partnerID=40&md5=51febb550a1cfd7909fd0ff26527f5b0},
  abstract = {This paper proposes a novel robust decentralized charging strategy for large-scale EV fleets. The system incorporates multiple EVs as well as inelastic loads connected to the power grid under power flow limits. We aim at minimizing both the overall charging energy payment and the aggregated battery degradation cost of EVs while preserving the robustness of the solution against uncertainties in the price of the electricity purchased from the power grid and the demand of inelastic loads. The proposed approach relies on the so-called uncertainty set-based robust optimization. The resulting charge scheduling problem is formulated as a tractable quadratic programming problem where all the EVs' decisions are coupled via the grid resource-sharing constraints and the robust counterpart supporting constraints. We adopt an extended Jacobi-Proximal Alternating Direction Method of Multipliers algorithm to solve effectively the formulated scheduling problem in a decentralized fashion, thus allowing the method applicability to large scale fleets. Simulations of a realistic case study show that the proposed approach not only reduces the costs of the EV fleet, but also maintains the robustness of the solution against perturbations in different uncertain parameters, which is beneficial for both EVs' users and the power grid. © 2020 IEEE.},
  author_keywords = {ADMM; Charge scheduling; Decentralized control; Electric vehicles; Large-scale optimization; Robust optimization; Set-based uncertainty},
  keywords = {Charging (batteries); Costs; Electric load flow; Quadratic programming; Scheduling; Uncertainty analysis; Alternating direction method of multipliers; Battery degradation; Charging energies; Charging strategies; Quadratic programming problems; Robust optimization; Scheduling problem; Uncertain parameters; Electric power transmission networks},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Dotoli, M., Epicoco, N. & Falagario, M. (2020) Multi-Criteria Decision Making techniques for the management of public procurement tenders: A case study. IN Applied Soft Computing Journal, 88.. doi:10.1016/j.asoc.2020.106064
  [BibTeX] [Abstract] [Download PDF]

  Multi-Criteria Decision Making (MCDM) techniques are mathematical tools that help decision makers evaluating and ranking in an automatic way many possible alternatives over multiple conflicting criteria in highly complex situations. Several MCDM approaches exist, and their application fields are numerous, including the Supplier Selection Problem (SSP), which is an important problem in the management field. The aim of this paper is to perform a comparative analysis among some selected well-known MCDM techniques to show how they can properly support the specific decision making process of Public Procurement (PP) tenders, which is a particular type of the SSP, characterized by very stringent rules, thus requiring a specific assessment. Indeed, PP is a field characterized by the need for transparency, objectivity, and non-discrimination, which requires tendering organizations to explicitly state the adopted awarding method, the chosen decision criteria, and their relative importance in the call for proposals. However, this field has been seldomly investigated in the pertinent literature and thus the aim of this paper is to overcome such a limitation. In particular, this work focuses on the most commonly adopted methods in the field of supplier selection, namely the Analytic Hierarchy Process (AHP), the Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), the Multi Attribute Utility Theory (MAUT), and the Data Envelopment Analysis (DEA). First, we adapt these techniques to the PP problem and its requirements. Then, by means of some real tenders at a European Institution, the selected techniques are compared with each other and with the currently adopted methodology in their classical deterministic setting, to identify which method best suits the specific requirements of PP tenders. Hence, since nowadays uncertainty is inherent in data from real applications, and can be modelled by expert evaluations through fuzzy logic, the comparison is extended to the fuzzy counterparts of two of the most promising selected approaches, i.e., the Fuzzy AHP and the Fuzzy DEA, showing that these methods can be effectively applied to the PP sector also in the presence of uncertainty on the tenders data. © 2020 Elsevier B.V.

  @ARTICLE{Dotoli2020,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco},
  title = {Multi-Criteria Decision Making techniques for the management of public procurement tenders: A case study},
  year = {2020},
  journal = {Applied Soft Computing Journal},
  volume = {88},
  doi = {10.1016/j.asoc.2020.106064},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077767281&doi=10.1016%2fj.asoc.2020.106064&partnerID=40&md5=eccbdda5b4995aaf45ca9d623d896b82},
  abstract = {Multi-Criteria Decision Making (MCDM) techniques are mathematical tools that help decision makers evaluating and ranking in an automatic way many possible alternatives over multiple conflicting criteria in highly complex situations. Several MCDM approaches exist, and their application fields are numerous, including the Supplier Selection Problem (SSP), which is an important problem in the management field. The aim of this paper is to perform a comparative analysis among some selected well-known MCDM techniques to show how they can properly support the specific decision making process of Public Procurement (PP) tenders, which is a particular type of the SSP, characterized by very stringent rules, thus requiring a specific assessment. Indeed, PP is a field characterized by the need for transparency, objectivity, and non-discrimination, which requires tendering organizations to explicitly state the adopted awarding method, the chosen decision criteria, and their relative importance in the call for proposals. However, this field has been seldomly investigated in the pertinent literature and thus the aim of this paper is to overcome such a limitation. In particular, this work focuses on the most commonly adopted methods in the field of supplier selection, namely the Analytic Hierarchy Process (AHP), the Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), the Multi Attribute Utility Theory (MAUT), and the Data Envelopment Analysis (DEA). First, we adapt these techniques to the PP problem and its requirements. Then, by means of some real tenders at a European Institution, the selected techniques are compared with each other and with the currently adopted methodology in their classical deterministic setting, to identify which method best suits the specific requirements of PP tenders. Hence, since nowadays uncertainty is inherent in data from real applications, and can be modelled by expert evaluations through fuzzy logic, the comparison is extended to the fuzzy counterparts of two of the most promising selected approaches, i.e., the Fuzzy AHP and the Fuzzy DEA, showing that these methods can be effectively applied to the PP sector also in the presence of uncertainty on the tenders data. © 2020 Elsevier B.V.},
  author_keywords = {Compensatory models; Multi-Criteria Decision Making; Public procurement},
  keywords = {Analytic hierarchy process; Data envelopment analysis; Fuzzy logic; Hierarchical systems; Analytic hierarchy process (ahp); Comparative analysis; Decision making process; European institutions; Multi criteria decision making; Multi-criteria decision making technique; Multiattribute utility theory; Public procurement; Decision making},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 63}
  }

• Dotoli, M. & Jia, Q. (2020) Guest Editorial Special Section on the 2017 International Conference on Automation Science and Engineering. IN IEEE Transactions on Automation Science and Engineering, 17.1095 – 1096. doi:10.1109/TASE.2020.2990785
  [BibTeX] [Download PDF]

  @ARTICLE{Dotoli20201095,
  author = {Dotoli, Mariagrazia and Jia, Qing-Shan},
  title = {Guest Editorial Special Section on the 2017 International Conference on Automation Science and Engineering},
  year = {2020},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {17},
  number = {3},
  pages = {1095 – 1096},
  doi = {10.1109/TASE.2020.2990785},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087616647&doi=10.1109%2fTASE.2020.2990785&partnerID=40&md5=d74ffa09fbe26897b73ee82716e7f402},
  type = {Editorial},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Bronze Open Access}
  }

• Scarabaggio, P., Carli, R., La Scala, M. & Dotoli, M. (2020) Effects of COVID-19 on electricity demand in Northern Italy; [Effetti del COVID-19 sulla domanda di energia elettrica nel Nord Italia]. IN Energia Elettrica, 97.41 – 51.
  [BibTeX] [Abstract] [Download PDF]

  Technical analysis of the effects of the COVID-19 pandemic on electricity demand: the case of Northern Italy. Estimation of the impact of social mobility on electricity consumption. Future challenges and prospects.

  @ARTICLE{Scarabaggio202041,
  author = {Scarabaggio, Paolo and Carli, Raffaele and La Scala, Massimo and Dotoli, Mariagrazia},
  title = {Effects of COVID-19 on electricity demand in Northern Italy; [Effetti del COVID-19 sulla domanda di energia elettrica nel Nord Italia]},
  year = {2020},
  journal = {Energia Elettrica},
  volume = {97},
  number = {5},
  pages = {41 – 51},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148942790&partnerID=40&md5=a3679ff0d5aca129d11834c5886fe935},
  abstract = {Technical analysis of the effects of the COVID-19 pandemic on electricity demand: the case of Northern Italy. Estimation of the impact of social mobility on electricity consumption. Future challenges and prospects.},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Carli, R. & Dotoli, M. (2020) Distributed Alternating Direction Method of Multipliers for Linearly Constrained Optimization over a Network. IN IEEE Control Systems Letters, 4.247 – 252. doi:10.1109/LCSYS.2019.2923078
  [BibTeX] [Abstract] [Download PDF]

  In this letter we address the distributed optimization problem for a network of agents, which commonly occurs in several control engineering applications. Differently from the related literature, where only consensus constraints are typically addressed, we consider a challenging distributed optimization set-up where agents rely on local communication and computation to optimize a sum of local objective functions, each depending on individual variables subject to local constraints, while satisfying linear coupling constraints. Thanks to the distributed scheme, the resolution of the optimization problem turns into designing an iterative control procedure that steers the strategies of agents-whose dynamics is decoupled-not only to be convergent to the optimal value but also to satisfy the coupling constraints. Based on duality and consensus theory, we develop a proximal Jacobian alternating direction method of multipliers (ADMM) for solving such a kind of linearly constrained convex optimization problems over a network. Using the monotone operator and fixed point mapping, we analyze the optimality of the proposed algorithm and establish its o(1/t) convergence rate. Finally, through numerical simulations we show that the proposed algorithm offers higher computational performances than recent distributed ADMM variants. © 2019 IEEE.

  @ARTICLE{Carli2020247,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Distributed Alternating Direction Method of Multipliers for Linearly Constrained Optimization over a Network},
  year = {2020},
  journal = {IEEE Control Systems Letters},
  volume = {4},
  number = {1},
  pages = {247 – 252},
  doi = {10.1109/LCSYS.2019.2923078},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068640431&doi=10.1109%2fLCSYS.2019.2923078&partnerID=40&md5=7f07a37d7f737276c9983542771cba08},
  abstract = {In this letter we address the distributed optimization problem for a network of agents, which commonly occurs in several control engineering applications. Differently from the related literature, where only consensus constraints are typically addressed, we consider a challenging distributed optimization set-up where agents rely on local communication and computation to optimize a sum of local objective functions, each depending on individual variables subject to local constraints, while satisfying linear coupling constraints. Thanks to the distributed scheme, the resolution of the optimization problem turns into designing an iterative control procedure that steers the strategies of agents-whose dynamics is decoupled-not only to be convergent to the optimal value but also to satisfy the coupling constraints. Based on duality and consensus theory, we develop a proximal Jacobian alternating direction method of multipliers (ADMM) for solving such a kind of linearly constrained convex optimization problems over a network. Using the monotone operator and fixed point mapping, we analyze the optimality of the proposed algorithm and establish its o(1/t) convergence rate. Finally, through numerical simulations we show that the proposed algorithm offers higher computational performances than recent distributed ADMM variants. © 2019 IEEE.},
  author_keywords = {Distributed control; distributed optimization; optimization algorithms},
  keywords = {Computation theory; Convex optimization; Iterative methods; Alternating direction method of multipliers; Computational performance; Constrained convex optimizations; Distributed control; Distributed optimization; Engineering applications; Linearly constrained optimization; Optimization algorithms; Constrained optimization},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 21}
  }

• Carli, R. & Dotoli, M. (2020) A Dynamic Programming Approach for the Decentralized Control of Energy Retrofit in Large-Scale Street Lighting Systems. IN IEEE Transactions on Automation Science and Engineering, 17.1140 – 1157. doi:10.1109/TASE.2020.2966738
  [BibTeX] [Abstract] [Download PDF]

  This article proposes a decision-making procedure that supports the city energy manager in determining the optimal energy retrofit plan of an existing public street lighting system throughout a wide urban area. The proposed decision model aims at simultaneously maximizing the energy consumption reduction and achieving an optimal allocation of the retrofit actions among the street lighting subsystems, while efficiently using the available budget. The resulting optimization problem is formulated as a quadratic knapsack problem. The proposed solution relies on a decentralized control algorithm that combines discrete dynamic programming with additive decomposition and value functions approximation. The optimality and complexity of the presented strategy are investigated, demonstrating that the proposed algorithm constitutes a fully polynomial approximation scheme. Simulation results related to a real street lighting system in the city of Bari (Italy) are presented to show the effectiveness of the approach in the optimal energy management of large-scale street lighting systems. Note to Practitioners-This article addresses the emerging need for decision support tools for the energy management of urban street lighting systems. The proposed decision-making strategy allows city energy managers and local policy makers taking retrofit decisions on an existing public street lighting system throughout a wide urban area. The presented strategy can be implemented in any engineering software, providing decision makers with a low-complexity and scalable Information and Communication Technology (ICT) tool for the optimization of the energy efficiency and environmental sustainability of street lighting systems. © 2004-2012 IEEE.

  @ARTICLE{Carli20201140,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A Dynamic Programming Approach for the Decentralized Control of Energy Retrofit in Large-Scale Street Lighting Systems},
  year = {2020},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {17},
  number = {3},
  pages = {1140 – 1157},
  doi = {10.1109/TASE.2020.2966738},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087543588&doi=10.1109%2fTASE.2020.2966738&partnerID=40&md5=b2d2ba1ad644c81f451c0936fe963e18},
  abstract = {This article proposes a decision-making procedure that supports the city energy manager in determining the optimal energy retrofit plan of an existing public street lighting system throughout a wide urban area. The proposed decision model aims at simultaneously maximizing the energy consumption reduction and achieving an optimal allocation of the retrofit actions among the street lighting subsystems, while efficiently using the available budget. The resulting optimization problem is formulated as a quadratic knapsack problem. The proposed solution relies on a decentralized control algorithm that combines discrete dynamic programming with additive decomposition and value functions approximation. The optimality and complexity of the presented strategy are investigated, demonstrating that the proposed algorithm constitutes a fully polynomial approximation scheme. Simulation results related to a real street lighting system in the city of Bari (Italy) are presented to show the effectiveness of the approach in the optimal energy management of large-scale street lighting systems. Note to Practitioners-This article addresses the emerging need for decision support tools for the energy management of urban street lighting systems. The proposed decision-making strategy allows city energy managers and local policy makers taking retrofit decisions on an existing public street lighting system throughout a wide urban area. The presented strategy can be implemented in any engineering software, providing decision makers with a low-complexity and scalable Information and Communication Technology (ICT) tool for the optimization of the energy efficiency and environmental sustainability of street lighting systems. © 2004-2012 IEEE.},
  author_keywords = {Decision-making; dynamic programming; energy management; fully polynomial approximation scheme; optimization; urban street lighting},
  keywords = {Approximation algorithms; Budget control; Combinatorial optimization; Decentralized control; Decision making; Decision support systems; Energy efficiency; Energy management; Energy management systems; Energy utilization; Green computing; Lighting fixtures; Managers; Polynomial approximation; Retrofitting; Street lighting; Sustainable development; Additive decomposition; Decision making procedure; Decision support tools; Decision-making strategies; Environmental sustainability; Information and Communication Technologies; Quadratic knapsack problems; Street lighting system; Dynamic programming},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 38}
  }

• Cavone, G., Dotoli, M., Epicoco, N., Morelli, D. & Seatzu, C. (2020) Design of Modern Supply Chain Networks Using Fuzzy Bargaining Game and Data Envelopment Analysis. IN IEEE Transactions on Automation Science and Engineering, 17.1221 – 1236. doi:10.1109/TASE.2020.2977452
  [BibTeX] [Abstract] [Download PDF]

  This article proposes a novel methodology for multistage, multiproduct, multi-item, and closed-loop Supply Chain Network (SCN) design under uncertainty. The method considers that multiple products are manufactured by the SCN, each composed by multiple items, and that some of the sold products may require repair, refurbishing, or remanufacturing activities. We solve the two main decisions that take place in the medium-/short-term planning horizon, namely partners’ selection and allocation of the received orders among them. The partners’ selection problem is solved by a cross-efficiency fuzzy Data Envelopment Analysis technique, which allows evaluating the efficiency of each SCN member and ranking them against multiple conflicting objectives under uncertain data on their performance. Then, according to the estimated customers’ demand, the order allocation problem is solved by a fuzzy bargaining game problem, where each SCN actor behaves to simultaneously maximize both its own profit and the service level of the overall SCN in terms of efficiency, costs, and lead time. An illustrative example from the literature is finally presented. Note to Practitioners-We present a decision tool to address the optimal design, performance evaluation, and continuous improvement of modern cooperative SCNs. We propose an effective method to jointly solve the members’ selection and the orders’ allocation, considering the complex structure of modern SCNs, the multiobjective nature of the problems, and the uncertainty characterizing economic markets. Competition within SCNs stages and cooperation along the chain are considered, with the aim to improve both financial and environmental sustainability, while ensuring the highest service levels to customers. © 2004-2012 IEEE.

  @ARTICLE{Cavone20201221,
  author = {Cavone, Graziana and Dotoli, Mariagrazia and Epicoco, Nicola and Morelli, Davide and Seatzu, Carla},
  title = {Design of Modern Supply Chain Networks Using Fuzzy Bargaining Game and Data Envelopment Analysis},
  year = {2020},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {17},
  number = {3},
  pages = {1221 – 1236},
  doi = {10.1109/TASE.2020.2977452},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087545403&doi=10.1109%2fTASE.2020.2977452&partnerID=40&md5=36c9b0b7af0bb44437e25bed1ffbd281},
  abstract = {This article proposes a novel methodology for multistage, multiproduct, multi-item, and closed-loop Supply Chain Network (SCN) design under uncertainty. The method considers that multiple products are manufactured by the SCN, each composed by multiple items, and that some of the sold products may require repair, refurbishing, or remanufacturing activities. We solve the two main decisions that take place in the medium-/short-term planning horizon, namely partners' selection and allocation of the received orders among them. The partners' selection problem is solved by a cross-efficiency fuzzy Data Envelopment Analysis technique, which allows evaluating the efficiency of each SCN member and ranking them against multiple conflicting objectives under uncertain data on their performance. Then, according to the estimated customers' demand, the order allocation problem is solved by a fuzzy bargaining game problem, where each SCN actor behaves to simultaneously maximize both its own profit and the service level of the overall SCN in terms of efficiency, costs, and lead time. An illustrative example from the literature is finally presented. Note to Practitioners-We present a decision tool to address the optimal design, performance evaluation, and continuous improvement of modern cooperative SCNs. We propose an effective method to jointly solve the members' selection and the orders' allocation, considering the complex structure of modern SCNs, the multiobjective nature of the problems, and the uncertainty characterizing economic markets. Competition within SCNs stages and cooperation along the chain are considered, with the aim to improve both financial and environmental sustainability, while ensuring the highest service levels to customers. © 2004-2012 IEEE.},
  author_keywords = {Bargaining game; fuzzy set theory; order allocation; supplier selection; Supply Chain Network Design (SCND)},
  keywords = {Data envelopment analysis; Efficiency; Supply chains; Sustainable development; Closed-loop supply chain networks; Conflicting objectives; Continuous improvements; Design under uncertainty; Environmental sustainability; Fuzzy data envelopment analysis; Selection problems; Supply chain network; Game theory},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 32}
  }

• Hosseini, S. M., Carli, R., Cavone, G. & Dotoli, M. (2020) Distributed control of electric vehicle fleets considering grid congestion and battery degradation. IN Internet Technology Letters, 3.. doi:10.1002/itl2.161
  [BibTeX] [Abstract] [Download PDF]

  Nowadays, developing coordinated optimal charging strategies for large-scale electric vehicle (EV) fleets is crucial to ensure the reliability and efficiency of power grids. This paper presents a novel fully distributed control strategy for the optimal charging of large-scale EV fleets aiming at the minimization of the aggregated charging cost and battery degradation, while satisfying the EVs’ individual load requirements and the overall grid congestion limits. We formulate the optimization problem as a convex quadratic programming problem where all the EVs’ decisions are coupled both via the objective function and some grid resource sharing constraints. Based on the distributed waterfilling approach, the proposed resolution algorithm requires a minimal shared information between EVs that communicate only with their neighbors without relying on a central aggregator, thus guaranteeing the EV users’ privacy. The performance of the proposed approach is evaluated through numerical experiments to validate its effectiveness in achieving a global optimum while respecting the grid constraints with a favorable computational efficiency. © 2020 John Wiley & Sons, Ltd.

  @ARTICLE{Hosseini2020,
  author = {Hosseini, Seyed M. and Carli, Raffaele and Cavone, Graziana and Dotoli, Mariagrazia},
  title = {Distributed control of electric vehicle fleets considering grid congestion and battery degradation},
  year = {2020},
  journal = {Internet Technology Letters},
  volume = {3},
  number = {3},
  doi = {10.1002/itl2.161},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087647927&doi=10.1002%2fitl2.161&partnerID=40&md5=a8266a663395bc58f3c3631dc8791c0a},
  abstract = {Nowadays, developing coordinated optimal charging strategies for large-scale electric vehicle (EV) fleets is crucial to ensure the reliability and efficiency of power grids. This paper presents a novel fully distributed control strategy for the optimal charging of large-scale EV fleets aiming at the minimization of the aggregated charging cost and battery degradation, while satisfying the EVs' individual load requirements and the overall grid congestion limits. We formulate the optimization problem as a convex quadratic programming problem where all the EVs' decisions are coupled both via the objective function and some grid resource sharing constraints. Based on the distributed waterfilling approach, the proposed resolution algorithm requires a minimal shared information between EVs that communicate only with their neighbors without relying on a central aggregator, thus guaranteeing the EV users' privacy. The performance of the proposed approach is evaluated through numerical experiments to validate its effectiveness in achieving a global optimum while respecting the grid constraints with a favorable computational efficiency. © 2020 John Wiley & Sons, Ltd.},
  author_keywords = {distributed control; electric vehicles; large-scale optimization; smart charging},
  keywords = {Charging (batteries); Computational efficiency; Electric machine control; Electric power transmission networks; Quadratic programming; Secondary batteries; Traffic congestion; Vehicle-to-grid; Battery degradation; Charging strategies; Distributed control strategy; Distributed-control; Large-scale optimization; Large-scales; Optimal charging; Power grids; Smart charging; Vehicle fleets; Electric vehicles},
  type = {Letter},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 13}
  }

• Scarabaggio, P., Grammatico, S., Carli, R. & Dotoli, M. (2020) A distributed, rolling-horizon demand side management algorithm under wind power uncertainty IN IFAC-PapersOnLine., 12620 – 12625. doi:10.1016/j.ifacol.2020.12.1830
  [BibTeX] [Abstract] [Download PDF]

  In this paper, we consider a smart grid where users behave selfishly, aiming at minimizing cost in the presence of uncertain wind power availability. We adopt a demand side management (DSM) model, where active users (so-called prosumers) have both private generation and local storage availability. These prosumers participate to the DSM strategy by updating their energy schedule, seeking to minimize their local cost, given their local preferences and the global grid constraints. The energy price is defined as a function of the aggregate load and the wind power availability. We model the resulting problem as a non-cooperative Nash game and propose a semi-decentralized algorithm to compute an equilibrium. To cope with the uncertainty in the wind power, we adopt a rolling-horizon approach, and in addition we use a stochastic optimization technique. We generate several wind power production scenarios from a defined probability density function (PDF), determining an approximate stochastic cost function. Simulations results on a real dataset show that the proposed approach generates lower individual costs compared to a standard expected value approach. Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license

  @CONFERENCE{Scarabaggio202012620,
  author = {Scarabaggio, Paolo and Grammatico, Sergio and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A distributed, rolling-horizon demand side management algorithm under wind power uncertainty},
  year = {2020},
  journal = {IFAC-PapersOnLine},
  volume = {53},
  number = {2},
  pages = {12620 – 12625},
  doi = {10.1016/j.ifacol.2020.12.1830},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105077171&doi=10.1016%2fj.ifacol.2020.12.1830&partnerID=40&md5=ee3d9dd2c0187078aed713ccc87a026b},
  abstract = {In this paper, we consider a smart grid where users behave selfishly, aiming at minimizing cost in the presence of uncertain wind power availability. We adopt a demand side management (DSM) model, where active users (so-called prosumers) have both private generation and local storage availability. These prosumers participate to the DSM strategy by updating their energy schedule, seeking to minimize their local cost, given their local preferences and the global grid constraints. The energy price is defined as a function of the aggregate load and the wind power availability. We model the resulting problem as a non-cooperative Nash game and propose a semi-decentralized algorithm to compute an equilibrium. To cope with the uncertainty in the wind power, we adopt a rolling-horizon approach, and in addition we use a stochastic optimization technique. We generate several wind power production scenarios from a defined probability density function (PDF), determining an approximate stochastic cost function. Simulations results on a real dataset show that the proposed approach generates lower individual costs compared to a standard expected value approach. Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license},
  author_keywords = {Demand side management; Sample average approximation; Smart grid; Stochastic optimization},
  keywords = {Approximation algorithms; Cost functions; Demand side management; Electric power transmission networks; Electric utilities; Optimization; Probability density function; Stochastic systems; Wind power; Energy; Management Model; Management strategies; Minimizing costs; Rolling horizon; Sample average approximation; Smart grid; Stochastic optimizations; Uncertainty; Wind power availability; Smart power grids},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3; All Open Access, Gold Open Access}
  }

• Scarabaggio, P., La Scala, M., Carli, R. & Dotoli, M. (2020) Analyzing the Effects of COVID-19 Pandemic on the Energy Demand: The Case of Northern Italy IN 12th AEIT International Annual Conference, AEIT 2020.. doi:10.23919/AEIT50178.2020.9241136
  [BibTeX] [Abstract] [Download PDF]

  The COVID-19 crisis is profoundly influencing the global economic framework due to restrictive measures adopted by governments worldwide. Finding real-time data to correctly quantify this impact is very significant but not as straightforward. Nevertheless, an analysis of the power demand profiles provides insight into the overall economic trends. To accurately assess the change in energy consumption patterns, in this work we employ a multi-layer feed-forward neural network that calculates an estimation of the aggregated power demand in the north of Italy, (i.e, in one of the European areas that were most affected by the pandemics) in the absence of the COVID-19 emergency. After assessing the forecasting model reliability, we compare the estimation with the ground truth data to quantify the variation in power consumption. Moreover, we correlate this variation with the change in mobility behaviors during the lockdown period by employing the Google mobility report data. From this unexpected and unprecedented situation, we obtain some intuition regarding the power system macro-structure and its relation with the overall people’s mobility. © 2020 AEIT.

  @CONFERENCE{Scarabaggio2020,
  author = {Scarabaggio, Paolo and La Scala, Massimo and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Analyzing the Effects of COVID-19 Pandemic on the Energy Demand: The Case of Northern Italy},
  year = {2020},
  journal = {12th AEIT International Annual Conference, AEIT 2020},
  doi = {10.23919/AEIT50178.2020.9241136},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097170993&doi=10.23919%2fAEIT50178.2020.9241136&partnerID=40&md5=a3abf95802bb66dc9a2d8715976cc126},
  abstract = {The COVID-19 crisis is profoundly influencing the global economic framework due to restrictive measures adopted by governments worldwide. Finding real-time data to correctly quantify this impact is very significant but not as straightforward. Nevertheless, an analysis of the power demand profiles provides insight into the overall economic trends. To accurately assess the change in energy consumption patterns, in this work we employ a multi-layer feed-forward neural network that calculates an estimation of the aggregated power demand in the north of Italy, (i.e, in one of the European areas that were most affected by the pandemics) in the absence of the COVID-19 emergency. After assessing the forecasting model reliability, we compare the estimation with the ground truth data to quantify the variation in power consumption. Moreover, we correlate this variation with the change in mobility behaviors during the lockdown period by employing the Google mobility report data. From this unexpected and unprecedented situation, we obtain some intuition regarding the power system macro-structure and its relation with the overall people's mobility. © 2020 AEIT.},
  author_keywords = {COVID-19; Lockdown; Machine learning; Neural networks; Power systems},
  keywords = {Electric power utilization; Energy utilization; Feedforward neural networks; Economic trends; Forecasting modeling; Global economics; Ground truth data; Macrostructures; Mobility behavior; Multilayer feedforward neural networks; Northern Italy; Multilayer neural networks},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 14; All Open Access, Green Open Access}
  }

• Carli, R., Cavone, G., Othman, S. B. & Dotoli, M. (2020) IoT based architecture for model predictive control of HVAC systems in smart buildings. IN Sensors (Switzerland), 20.. doi:10.3390/s20030781
  [BibTeX] [Abstract] [Download PDF]

  The efficient management of Heating Ventilation and Air Conditioning (HVAC) systems in smart buildings is one of the main applications of the Internet of Things (IoT) paradigm. In this paper we propose an IoT based architecture for the implementation of Model Predictive Control (MPC) of HVAC systems in real environments. The considered MPC algorithm optimizes on line, in a closed-loop control fashion, both the indoor thermal comfort and the related energy consumption for a single zone environment. Thanks to the proposed IoT based architecture, the sensing, control, and actuating subsystems are all connected to the Internet, and a remote interface with the HVAC control system is guaranteed to end-users. In particular, sensors and actuators communicate with a remote database server and a control unit, which provides the control actions to be actuated in the HVAC system; users can set remotely the control mode and related set-points of the system; while comfort and environmental indices are transferred via the Internet and displayed on the end-users’ interface. The proposed IoT based control architecture is implemented and tested in a campus building at the Polytechnic of Bari (Italy) in a proof of concept perspective. The effectiveness of the proposed control algorithm is assessed in the real environment evaluating both the thermal comfort results and the energy savings with respect to a classical thermostat regulation approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

  @ARTICLE{Carli2020,
  author = {Carli, Raffaele and Cavone, Graziana and Othman, Sarah Ben and Dotoli, Mariagrazia},
  title = {IoT based architecture for model predictive control of HVAC systems in smart buildings},
  year = {2020},
  journal = {Sensors (Switzerland)},
  volume = {20},
  number = {3},
  doi = {10.3390/s20030781},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079071499&doi=10.3390%2fs20030781&partnerID=40&md5=b68287ad61a3091865fc7546425dce95},
  abstract = {The efficient management of Heating Ventilation and Air Conditioning (HVAC) systems in smart buildings is one of the main applications of the Internet of Things (IoT) paradigm. In this paper we propose an IoT based architecture for the implementation of Model Predictive Control (MPC) of HVAC systems in real environments. The considered MPC algorithm optimizes on line, in a closed-loop control fashion, both the indoor thermal comfort and the related energy consumption for a single zone environment. Thanks to the proposed IoT based architecture, the sensing, control, and actuating subsystems are all connected to the Internet, and a remote interface with the HVAC control system is guaranteed to end-users. In particular, sensors and actuators communicate with a remote database server and a control unit, which provides the control actions to be actuated in the HVAC system; users can set remotely the control mode and related set-points of the system; while comfort and environmental indices are transferred via the Internet and displayed on the end-users’ interface. The proposed IoT based control architecture is implemented and tested in a campus building at the Polytechnic of Bari (Italy) in a proof of concept perspective. The effectiveness of the proposed control algorithm is assessed in the real environment evaluating both the thermal comfort results and the energy savings with respect to a classical thermostat regulation approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
  author_keywords = {Heating ventilation and air conditioning system; Internet of things; Model predictive control; Predicted mean vote; Smart buildings},
  keywords = {Air conditioning; Closed loop control systems; Energy conservation; Energy utilization; Heat pump systems; HVAC; Intelligent buildings; Model predictive control; Predictive control systems; Thermal comfort; Closed-loop control; Control architecture; Efficient managements; Heating ventilation and air conditioning; Indoor thermal comfort; Internet of thing (IOT); Predicted mean vote; Sensors and actuators; Internet of things},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 96; All Open Access, Gold Open Access}
  }

• Carli, R., Dotoli, M., Digiesi, S., Facchini, F. & Mossa, G. (2020) Sustainable scheduling of material handling activities in labor-intensive warehouses: A decision and control model. IN Sustainability (Switzerland), 12.. doi:10.3390/SU12083111
  [BibTeX] [Abstract] [Download PDF]

  In recent years, the continuous increase of greenhouse gas emissions has led many companies to investigate the activities that have the greatest impact on the environment. Recent studies estimate that around 10% of worldwide CO2 emissions derive from logistical supply chains. The considerable amount of energy required for heating, cooling, and lighting as well as material handling equipment (MHE) in warehouses represents about 20% of the overall logistical costs. The reduction of warehouses’ energy consumption would thus lead to a significant benefit from an environmental point of view. In this context, sustainable strategies allowing the minimization of the cost of energy consumption due to MHE represent a new challenge in warehouse management. Consistent with this purpose, a two-step optimization model based on integer programming is developed in this paper to automatically identify an optimal schedule of the material handling activities of electric mobile MHEs (MMHEs) (i.e., forklifts) in labor-intensive warehouses from profit and sustainability perspectives. The resulting scheduling aims at minimizing the total cost, which is the sum of the penalty cost related to the makespan of the material handling activities and the total electricity cost of charging batteries. The approach ensures that jobs are executed in accordance with priority queuing and that the completion time of battery recharging is minimized. Realistic numerical experiments are conducted to evaluate the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. The obtained results show the effectiveness of the model in identifying the optimal battery-charging schedule for a fleet of electric MMHEs from economic and environmental perspectives simultaneously. © 2020 by the authors.

  @ARTICLE{Carli2020,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Digiesi, Salvatore and Facchini, Francesco and Mossa, Giorgio},
  title = {Sustainable scheduling of material handling activities in labor-intensive warehouses: A decision and control model},
  year = {2020},
  journal = {Sustainability (Switzerland)},
  volume = {12},
  number = {8},
  doi = {10.3390/SU12083111},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084607073&doi=10.3390%2fSU12083111&partnerID=40&md5=225791095c6b1ea49a9be39370e2fff5},
  abstract = {In recent years, the continuous increase of greenhouse gas emissions has led many companies to investigate the activities that have the greatest impact on the environment. Recent studies estimate that around 10% of worldwide CO2 emissions derive from logistical supply chains. The considerable amount of energy required for heating, cooling, and lighting as well as material handling equipment (MHE) in warehouses represents about 20% of the overall logistical costs. The reduction of warehouses' energy consumption would thus lead to a significant benefit from an environmental point of view. In this context, sustainable strategies allowing the minimization of the cost of energy consumption due to MHE represent a new challenge in warehouse management. Consistent with this purpose, a two-step optimization model based on integer programming is developed in this paper to automatically identify an optimal schedule of the material handling activities of electric mobile MHEs (MMHEs) (i.e., forklifts) in labor-intensive warehouses from profit and sustainability perspectives. The resulting scheduling aims at minimizing the total cost, which is the sum of the penalty cost related to the makespan of the material handling activities and the total electricity cost of charging batteries. The approach ensures that jobs are executed in accordance with priority queuing and that the completion time of battery recharging is minimized. Realistic numerical experiments are conducted to evaluate the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. The obtained results show the effectiveness of the model in identifying the optimal battery-charging schedule for a fleet of electric MMHEs from economic and environmental perspectives simultaneously. © 2020 by the authors.},
  author_keywords = {Battery charging; Decision and control; Demand-side management; Green warehouse; Material handling activity; Mobile material handling equipment; Optimization; Sustainable scheduling; Warehouse energy management},
  keywords = {carbon dioxide; carbon emission; cooling; cost analysis; decision making; environmental economics; environmental impact; equipment; fuel consumption; greenhouse gas; heating; optimization; strategic approach; supply chain management; sustainability},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 27; All Open Access, Gold Open Access}
  }

• Ben Cheikh-Graiet, S., Dotoli, M. & Hammadi, S. (2020) A Tabu Search based metaheuristic for dynamic carpooling optimization. IN Computers and Industrial Engineering, 140.. doi:10.1016/j.cie.2019.106217
  [BibTeX] [Abstract] [Download PDF]

  The carpooling problem consists in matching a set of riders’ requests with a set of drivers’ offers by synchro-nizing their origins, destinations and time windows. The paper presents the so-called Dynamic Carpooling Optimization System (DyCOS), a system which supports the automatic and optimal ridematching process be-tween users on very short notice or even en-route. Nowadays, there are numerous research contributions that revolve around the carpooling problem, notably in the dynamic context. However, the problem’s high complex-ity and the real time aspect are still challenges to overcome when addressing dynamic carpooling. To counter these issues, DyCOS takes decisions using a novel Tabu Search based metaheuristic. The proposed algorithm employs an explicit memory system and several original searching strategies developed to make optimal deci-sions automatically. To increase users’ satisfaction, the proposed metaheuristic approach manages the transfer process and includes the possibility to drop off the passenger at a given walking distance from his destination or at a transfer node. In addition, the detour concept is used as an original aspiration process, to avoid the entrapment by local solutions and improve the generated solution. For a rigorous assessment of generated so-lutions, while considering the importance and interaction among the optimization criteria, the algorithm adopts the Choquet integral operator as an aggregation approach. To measure the effectiveness of the proposed method, we develop a simulation environment based on actual carpooling demand data from the metropolitan area of Lille in the north of France. © 2020 Elsevier Ltd

  @ARTICLE{Ben Cheikh-Graiet2020,
  author = {Ben Cheikh-Graiet, Sondes and Dotoli, Mariagrazia and Hammadi, Slim},
  title = {A Tabu Search based metaheuristic for dynamic carpooling optimization},
  year = {2020},
  journal = {Computers and Industrial Engineering},
  volume = {140},
  doi = {10.1016/j.cie.2019.106217},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077798452&doi=10.1016%2fj.cie.2019.106217&partnerID=40&md5=2652f6e49f0547e51b9a72ee41646328},
  abstract = {The carpooling problem consists in matching a set of riders’ requests with a set of drivers’ offers by synchro-nizing their origins, destinations and time windows. The paper presents the so-called Dynamic Carpooling Optimization System (DyCOS), a system which supports the automatic and optimal ridematching process be-tween users on very short notice or even en-route. Nowadays, there are numerous research contributions that revolve around the carpooling problem, notably in the dynamic context. However, the problem's high complex-ity and the real time aspect are still challenges to overcome when addressing dynamic carpooling. To counter these issues, DyCOS takes decisions using a novel Tabu Search based metaheuristic. The proposed algorithm employs an explicit memory system and several original searching strategies developed to make optimal deci-sions automatically. To increase users’ satisfaction, the proposed metaheuristic approach manages the transfer process and includes the possibility to drop off the passenger at a given walking distance from his destination or at a transfer node. In addition, the detour concept is used as an original aspiration process, to avoid the entrapment by local solutions and improve the generated solution. For a rigorous assessment of generated so-lutions, while considering the importance and interaction among the optimization criteria, the algorithm adopts the Choquet integral operator as an aggregation approach. To measure the effectiveness of the proposed method, we develop a simulation environment based on actual carpooling demand data from the metropolitan area of Lille in the north of France. © 2020 Elsevier Ltd},
  author_keywords = {Automatic ridematching; Choquet integral; Dynamic ridesharing; Multi-criterion optimization; Tabu search},
  keywords = {Dysprosium compounds; Integral equations; Tabu search; Automatic ridematching; Choquet integral; Meta-heuristic approach; Multi-criterion optimization; Optimization criteria; Optimization system; Ride-sharing; Simulation environment; Sulfur compounds},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 32; All Open Access, Green Open Access}
  }

• Scarabaggio, P., Carli, R. & Dotoli, M. (2020) A game-theoretic control approach for the optimal energy storage under power flow constraints in distribution networks IN IEEE International Conference on Automation Science and Engineering., 1281 – 1286. doi:10.1109/CASE48305.2020.9216800
  [BibTeX] [Abstract] [Download PDF]

  Traditionally, the management of power distribution networks relies on the centralized implementation of the optimal power flow and, in particular, the minimization of the generation cost and transmission losses. Nevertheless, the increasing penetration of both renewable energy sources and independent players such as ancillary service providers in modern networks have made this centralized framework inadequate. Against this background, we propose a noncooperative game-theoretic framework for optimally controlling energy storage systems (ESSs) in power distribution networks. Specifically, in this paper we address a power grid model that comprehends traditional loads, distributed generation sources and several independent energy storage providers, each owning an individual ESS. Through a rolling-horizon approach, the latter participate in the grid optimization process, aiming both at increasing the penetration of distributed generation and leveling the power injection from the transmission grid. Our framework incorporates not only economic factors but also grid stability aspects, including the power flow constraints. The paper fully describes the distribution grid model as well as the underlying market hypotheses and policies needed to force the energy storage providers to find a feasible equilibrium for the network. Numerical experiments based on the IEEE 33-bus system confirm the effectiveness and resiliency of the proposed framework. © 2020 IEEE.

  @CONFERENCE{Scarabaggio20201281,
  author = {Scarabaggio, Paolo and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A game-theoretic control approach for the optimal energy storage under power flow constraints in distribution networks},
  year = {2020},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2020-August},
  pages = {1281 – 1286},
  doi = {10.1109/CASE48305.2020.9216800},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094128798&doi=10.1109%2fCASE48305.2020.9216800&partnerID=40&md5=e4802c482f96ac90afd6c7a2c7f2b199},
  abstract = {Traditionally, the management of power distribution networks relies on the centralized implementation of the optimal power flow and, in particular, the minimization of the generation cost and transmission losses. Nevertheless, the increasing penetration of both renewable energy sources and independent players such as ancillary service providers in modern networks have made this centralized framework inadequate. Against this background, we propose a noncooperative game-theoretic framework for optimally controlling energy storage systems (ESSs) in power distribution networks. Specifically, in this paper we address a power grid model that comprehends traditional loads, distributed generation sources and several independent energy storage providers, each owning an individual ESS. Through a rolling-horizon approach, the latter participate in the grid optimization process, aiming both at increasing the penetration of distributed generation and leveling the power injection from the transmission grid. Our framework incorporates not only economic factors but also grid stability aspects, including the power flow constraints. The paper fully describes the distribution grid model as well as the underlying market hypotheses and policies needed to force the energy storage providers to find a feasible equilibrium for the network. Numerical experiments based on the IEEE 33-bus system confirm the effectiveness and resiliency of the proposed framework. © 2020 IEEE.},
  keywords = {Data storage equipment; Distributed power generation; Electric load flow; Electric network analysis; Electric power system economics; Electric power transmission; Energy storage; Game theory; Renewable energy resources; Storage as a service (STaaS); Distributed generation source; Energy Storage Systems (ESSs); Noncooperative game; Numerical experiments; Optimal power flows; Power distribution network; Renewable energy source; Transmission grids; Electric power transmission networks},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Carli, R., Cavone, G., Epicoco, N., Di Ferdinando, M., Scarabaggio, P. & Dotoli, M. (2020) Consensus-Based Algorithms for Controlling Swarms of Unmanned Aerial Vehicles. IN Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12338 LNCS.84 – 99. doi:10.1007/978-3-030-61746-2_7
  [BibTeX] [Abstract] [Download PDF]

  Multiple Unmanned Aerial Vehicles (multi-UAVs) applications are recently growing in several fields, ranging from military and rescue missions, remote sensing, and environmental surveillance, to meteorology, logistics, and farming. Overcoming the limitations on battery lifespan and on-board processor capabilities, the coordinated use of multi-UAVs is indeed more suitable than employing a single UAV in certain tasks. Hence, the research on swarm of UAVs is receiving increasing attention, including multidisciplinary aspects, such as coordination, aggregation, network communication, path planning, information sensing, and data fusion. The focus of this paper is on defining novel control strategies for the deployment of multi-UAV systems in a distributed time-varying set-up, where UAVs rely on local communication and computation. In particular, modeling the dynamics of each UAV by a discrete-time integrator, we analyze the main swarm intelligence strategies, namely flight formation, swarm tracking, and social foraging. First, we define a distributed control strategy for steering the agents of the swarm towards a collection point. Then, we cope with the formation control, defining a procedure to arrange agents in a family of geometric formations, where the distance between each pair of UAVs is predefined. Subsequently, we focus on swarm tracking, defining a distributed mechanism based on the so-called leader-following consensus to move the entire swarm in accordance with a predefined trajectory. Moreover, we define a social foraging strategy that allows agents to avoid obstacles, by imposing on-line a time-varying formation pattern. Finally, through numerical simulations we show the effectiveness of the proposed algorithms. © 2020, Springer Nature Switzerland AG.

  @ARTICLE{Carli202084,
  author = {Carli, Raffaele and Cavone, Graziana and Epicoco, Nicola and Di Ferdinando, Mario and Scarabaggio, Paolo and Dotoli, Mariagrazia},
  title = {Consensus-Based Algorithms for Controlling Swarms of Unmanned Aerial Vehicles},
  year = {2020},
  journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
  volume = {12338 LNCS},
  pages = {84 – 99},
  doi = {10.1007/978-3-030-61746-2_7},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093852465&doi=10.1007%2f978-3-030-61746-2_7&partnerID=40&md5=1c7da6000e4015880227c1eafe608f20},
  abstract = {Multiple Unmanned Aerial Vehicles (multi-UAVs) applications are recently growing in several fields, ranging from military and rescue missions, remote sensing, and environmental surveillance, to meteorology, logistics, and farming. Overcoming the limitations on battery lifespan and on-board processor capabilities, the coordinated use of multi-UAVs is indeed more suitable than employing a single UAV in certain tasks. Hence, the research on swarm of UAVs is receiving increasing attention, including multidisciplinary aspects, such as coordination, aggregation, network communication, path planning, information sensing, and data fusion. The focus of this paper is on defining novel control strategies for the deployment of multi-UAV systems in a distributed time-varying set-up, where UAVs rely on local communication and computation. In particular, modeling the dynamics of each UAV by a discrete-time integrator, we analyze the main swarm intelligence strategies, namely flight formation, swarm tracking, and social foraging. First, we define a distributed control strategy for steering the agents of the swarm towards a collection point. Then, we cope with the formation control, defining a procedure to arrange agents in a family of geometric formations, where the distance between each pair of UAVs is predefined. Subsequently, we focus on swarm tracking, defining a distributed mechanism based on the so-called leader-following consensus to move the entire swarm in accordance with a predefined trajectory. Moreover, we define a social foraging strategy that allows agents to avoid obstacles, by imposing on-line a time-varying formation pattern. Finally, through numerical simulations we show the effectiveness of the proposed algorithms. © 2020, Springer Nature Switzerland AG.},
  author_keywords = {Swarm intelligence; Trajectory control; Unmanned Aerial Vehicles},
  keywords = {Aircraft detection; Antennas; Data fusion; Distributed parameter control systems; Military applications; Military vehicles; Remote sensing; Unmanned aerial vehicles (UAV); Control strategies; Discrete-time integrators; Distributed control strategy; Environmental surveillance; Local communications; Network communications; Onboard processors; Time-varying formations; Mobile ad hoc networks},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 19}
  }

2019

• Hosseini, S. M., Carli, R. & Dotoli, M. (2019) Robust day-ahead energy scheduling of a smart residential user under uncertainty IN 2019 18th European Control Conference, ECC 2019., 935 – 940. doi:10.23919/ECC.2019.8796182
  [BibTeX] [Abstract] [Download PDF]

  This paper develops a robust optimization framework for the day-ahead energy scheduling of a grid-connected residential user. The system incorporates a renewable energy source (RES), a battery energy storage system (BESS) as well as elastic controllable and critical noncontrollable electrical appliances. The proposed approach copes with the fluctuation and intermittence of the RES generation and non-controllable load demand by a tractable robust optimization scheme requiring minimum information on the sources of uncertainty. The main objective is minimizing the total energy payment for the user considering operational/technical constraints and a contractual constraint penalizing the excessive use of energy. The presented framework allows the decision maker to define different robustness levels for uncertain variables, and to flexibly establish an equilibrium between user’s payment and price of robustness. To validate the effectiveness of the proposed framework under uncertainty, we simulate the dynamics of a residential user as a case study. A comparison between the proposed robust approach and the same method with deterministic RES and loads profiles is carried out and discussed. © 2019 EUCA.

  @CONFERENCE{Hosseini2019935,
  author = {Hosseini, Seyed Mohsen and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Robust day-ahead energy scheduling of a smart residential user under uncertainty},
  year = {2019},
  journal = {2019 18th European Control Conference, ECC 2019},
  pages = {935 – 940},
  doi = {10.23919/ECC.2019.8796182},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071523023&doi=10.23919%2fECC.2019.8796182&partnerID=40&md5=dbaf920bef232ca07b714d294ec35e28},
  abstract = {This paper develops a robust optimization framework for the day-ahead energy scheduling of a grid-connected residential user. The system incorporates a renewable energy source (RES), a battery energy storage system (BESS) as well as elastic controllable and critical noncontrollable electrical appliances. The proposed approach copes with the fluctuation and intermittence of the RES generation and non-controllable load demand by a tractable robust optimization scheme requiring minimum information on the sources of uncertainty. The main objective is minimizing the total energy payment for the user considering operational/technical constraints and a contractual constraint penalizing the excessive use of energy. The presented framework allows the decision maker to define different robustness levels for uncertain variables, and to flexibly establish an equilibrium between user's payment and price of robustness. To validate the effectiveness of the proposed framework under uncertainty, we simulate the dynamics of a residential user as a case study. A comparison between the proposed robust approach and the same method with deterministic RES and loads profiles is carried out and discussed. © 2019 EUCA.},
  keywords = {Decision making; Optimization; Renewable energy resources; Robustness (control systems); Scheduling; Battery energy storage systems; Controllable loads; Electrical appliances; Minimum information; Renewable energy source; Robust optimization; Sources of uncertainty; Uncertain variables; Housing},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 31}
  }

• Dotoli, M. & Epicoco, N. (2019) Emerging issues in control, decision, and ICT Approaches for smart waste management IN 2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019., 446 – 451. doi:10.1109/CoDIT.2019.8820603
  [BibTeX] [Abstract] [Download PDF]

  Waste management is one of the major concerns of our times. This paper investigates the main issues in waste management, the classical practices and their limitations, and highlights the recent trends in the field to identify the foremost research areas whose advancement will lead to the achievement of smart waste management systems. © 2019 IEEE.

  @CONFERENCE{Dotoli2019446,
  author = {Dotoli, M. and Epicoco, N.},
  title = {Emerging issues in control, decision, and ICT Approaches for smart waste management},
  year = {2019},
  journal = {2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019},
  pages = {446 – 451},
  doi = {10.1109/CoDIT.2019.8820603},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072826787&doi=10.1109%2fCoDIT.2019.8820603&partnerID=40&md5=09b23d63ad01f03c3b7e5a6d6065ce50},
  abstract = {Waste management is one of the major concerns of our times. This paper investigates the main issues in waste management, the classical practices and their limitations, and highlights the recent trends in the field to identify the foremost research areas whose advancement will lead to the achievement of smart waste management systems. © 2019 IEEE.},
  keywords = {Control engineering; In-control; Recent trends; Waste management systems; Waste management},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Cavone, G., Blenkers, L., Van Den Boom, T., Dotoli, M., Seatzu, C. & De Schutter, B. (2019) Railway disruption: A bi-level rescheduling algorithm IN 2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019., 54 – 59. doi:10.1109/CoDIT.2019.8820380
  [BibTeX] [Abstract] [Download PDF]

  The real-time rescheduling of railway traffic in case of unexpected events is a challenging task. This is mainly due to the complexity of the railway service, which has to ensure safety, punctuality, and efficiency to customers by respecting timetable, framework, and resources constraints. Most of the available researches focus on short delays (i.e., disturbances). Approaches typically rely on simplified macroscopic models for large-scale systems or detailed microscopic models for one or a few lines, due to the long computation time required for solving the rescheduling problem. Only a small number of works consider rescheduling in case of long delays (i.e., disruptions) and all of them are also based on either a macroscopic or a microscopic model. This research focuses on disruptions and aims at filling the gap between macroscopic and microscopic modelling by proposing an innovative bi-level rescheduling algorithm based on a mesoscopic Mixed Integer Linear Programming (MILP) model. The technique allows obtaining a feasible rescheduled timetable in a short computation time respecting not only timetable and safety constraints (typical of macroscopic models) but also capacity and ordering constraints for the disrupted stations (typical of microscopic models). The bi-level algorithm first solves the macroscopic MILP rescheduling problem and then, considering the cancellation and non-admissible platform assignments results, it solves a mesoscopic MILP rescheduling problem. This allows to significantly reduce the search space and consequently the computation time. The method is tested for the rescheduling of the Dutch railway traffic in case of a full blockade between two consecutive stations. © 2019 IEEE.

  @CONFERENCE{Cavone201954,
  author = {Cavone, G. and Blenkers, L. and Van Den Boom, T. and Dotoli, M. and Seatzu, C. and De Schutter, B.},
  title = {Railway disruption: A bi-level rescheduling algorithm},
  year = {2019},
  journal = {2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019},
  pages = {54 – 59},
  doi = {10.1109/CoDIT.2019.8820380},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072825857&doi=10.1109%2fCoDIT.2019.8820380&partnerID=40&md5=1402c9b7c47196a37e50ebaba061fdef},
  abstract = {The real-time rescheduling of railway traffic in case of unexpected events is a challenging task. This is mainly due to the complexity of the railway service, which has to ensure safety, punctuality, and efficiency to customers by respecting timetable, framework, and resources constraints. Most of the available researches focus on short delays (i.e., disturbances). Approaches typically rely on simplified macroscopic models for large-scale systems or detailed microscopic models for one or a few lines, due to the long computation time required for solving the rescheduling problem. Only a small number of works consider rescheduling in case of long delays (i.e., disruptions) and all of them are also based on either a macroscopic or a microscopic model. This research focuses on disruptions and aims at filling the gap between macroscopic and microscopic modelling by proposing an innovative bi-level rescheduling algorithm based on a mesoscopic Mixed Integer Linear Programming (MILP) model. The technique allows obtaining a feasible rescheduled timetable in a short computation time respecting not only timetable and safety constraints (typical of macroscopic models) but also capacity and ordering constraints for the disrupted stations (typical of microscopic models). The bi-level algorithm first solves the macroscopic MILP rescheduling problem and then, considering the cancellation and non-admissible platform assignments results, it solves a mesoscopic MILP rescheduling problem. This allows to significantly reduce the search space and consequently the computation time. The method is tested for the rescheduling of the Dutch railway traffic in case of a full blockade between two consecutive stations. © 2019 IEEE.},
  keywords = {Large scale systems; Railroad transportation; Railroads; Scheduling; Superconducting materials; Macroscopic and microscopic; Microscopic modeling; Microscopic models; Mixed integer linear programming model; Ordering constraints; Platform assignments; Real-time rescheduling; Rescheduling problem; Integer programming},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 19}
  }

• Hosseini, S. M., Carli, R. & Dotoli, M. (2019) A residential demand-side management strategy under nonlinear pricing based on robust model predictive control IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 3243 – 3248. doi:10.1109/SMC.2019.8913892
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a real-time demand side management framework based on robust model predictive control (RMPC) for residential smart grids. The system incorporates a number of interconnected smart homes, each equipped with controllable and non-controllable loads, as well as a shared energy storage system (ESS). We aim at minimizing the users’ energy payment and limiting the peak-to-average ratio (PAR) of the energy consumption while taking into account all device/comfort/contractual constraints, specifically the feasibility constraints on energy transferred between users and the power grid in presence of load demand uncertainty. We consider a quadratic cost function for energy bought from the grid. Firstly, the energy price and related constraints of the system are modeled. Then, a min-max robust problem is established to optimally schedule energy under an interval-based uncertainty set. We finally adopt model predictive control (MPC) to solve the resulting robust optimization problem iteratively over a finite-horizon time window based on the receding horizon concept. Moreover, the robustness of the proposed real-time approach against the level of conservativeness of the solution is addressed. The effectiveness of the method is validated through a simulated case study. © 2019 IEEE.

  @CONFERENCE{Hosseini20193243,
  author = {Hosseini, Seyed Mohsen and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A residential demand-side management strategy under nonlinear pricing based on robust model predictive control},
  year = {2019},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {2019-October},
  pages = {3243 – 3248},
  doi = {10.1109/SMC.2019.8913892},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076744329&doi=10.1109%2fSMC.2019.8913892&partnerID=40&md5=b8658f66ca7439fa6e7d9b02705e1b91},
  abstract = {This paper presents a real-time demand side management framework based on robust model predictive control (RMPC) for residential smart grids. The system incorporates a number of interconnected smart homes, each equipped with controllable and non-controllable loads, as well as a shared energy storage system (ESS). We aim at minimizing the users' energy payment and limiting the peak-to-average ratio (PAR) of the energy consumption while taking into account all device/comfort/contractual constraints, specifically the feasibility constraints on energy transferred between users and the power grid in presence of load demand uncertainty. We consider a quadratic cost function for energy bought from the grid. Firstly, the energy price and related constraints of the system are modeled. Then, a min-max robust problem is established to optimally schedule energy under an interval-based uncertainty set. We finally adopt model predictive control (MPC) to solve the resulting robust optimization problem iteratively over a finite-horizon time window based on the receding horizon concept. Moreover, the robustness of the proposed real-time approach against the level of conservativeness of the solution is addressed. The effectiveness of the method is validated through a simulated case study. © 2019 IEEE.},
  keywords = {Automation; Cost functions; Costs; Demand side management; Electric power transmission networks; Electric utilities; Energy utilization; Housing; Intelligent buildings; Iterative methods; Optimization; Predictive control systems; Robust control; Controllable loads; Energy storage systems; Non-linear pricing; Peak to average ratios; Quadratic cost functions; Robust model predictive control; Robust model predictive controls (RMPC); Robust optimization; Model predictive control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 32}
  }

• Carli, R., Dotoli, M. & Palmisano, V. (2019) A distributed control approach based on game theory for the optimal energy scheduling of a residential microgrid with shared generation and storage IN IEEE International Conference on Automation Science and Engineering., 960 – 965. doi:10.1109/COASE.2019.8843141
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a distributed control approach based on game theory for the energy scheduling of demand-side consumers sharing energy production and storage while purchasing further energy from the grid. The interaction between the controllers of consumers’ loads and the manager of shared energy resources is modeled as a two-level game. The competition among consumers is formulated as a noncooperative game, while the interaction between the consumers’ loads and the shared resources manager is formulated as a cooperative game. optimization problems are stated for each player to determine their own optimal strategies. The algorithms for loads controllers and shared resources’ manager are implemented through a distributed approach. Numerical experiments show the effectiveness of the proposed scheme. © 2019 IEEE.

  @CONFERENCE{Carli2019960,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Palmisano, Vittorio},
  title = {A distributed control approach based on game theory for the optimal energy scheduling of a residential microgrid with shared generation and storage},
  year = {2019},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2019-August},
  pages = {960 – 965},
  doi = {10.1109/COASE.2019.8843141},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072980491&doi=10.1109%2fCOASE.2019.8843141&partnerID=40&md5=52d9b8791bf4c74bacd4b6c99e48e8b9},
  abstract = {This paper presents a distributed control approach based on game theory for the energy scheduling of demand-side consumers sharing energy production and storage while purchasing further energy from the grid. The interaction between the controllers of consumers' loads and the manager of shared energy resources is modeled as a two-level game. The competition among consumers is formulated as a noncooperative game, while the interaction between the consumers' loads and the shared resources manager is formulated as a cooperative game. optimization problems are stated for each player to determine their own optimal strategies. The algorithms for loads controllers and shared resources' manager are implemented through a distributed approach. Numerical experiments show the effectiveness of the proposed scheme. © 2019 IEEE.},
  keywords = {Controllers; Energy resources; Managers; Scheduling; Distributed approaches; Distributed control; Energy productions; Noncooperative game; Numerical experiments; Optimal strategies; Optimization problems; Residential microgrid; Game theory},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

• Carli, R., Dotoli, M. & Pellegrino, R. (2019) A multi-period approach for the optimal energy retrofit planning of street lighting systems. IN Applied Sciences (Switzerland), 9.. doi:10.3390/app9051025
  [BibTeX] [Abstract] [Download PDF]

  Investing in the optimal measures for improving the energy efficiency of urban street lighting systems has become strategic for the economic, technological and social development of cities. The decision-making process for the selection of the optimal set of interventions is not so straightforward. Several criticalities-such as difficulties getting access to credit for companies involved in street lighting systems refurbishment, budget constraints of municipalities, and unawareness of the actual energy and economic performance after a retrofitting intervention-require a decision-making approach that supports the city energy manager in selecting the optimal street lighting energy efficiency retrofitting solution while looking not only based on the available budget, but also based on the future savings in energy expenditures. In this context, the purpose of our research is to develop an effective decision-making model supporting the optimal multi-period planning of the street lighting energy efficiency retrofitting, which proves to be more effective and beneficial than the classical single-period approach and has never before been applied to the considered public lighting system context. The proposed methodology is applied to a real street lighting system in the city of Bari, Italy, showing the energy savings and financial benefit obtained through the proposed method. Numerical experiments are used to investigate and quantify the effects of using a multi-period planning approach instead of a single-period approach. © 2019 by the authors.

  @ARTICLE{Carli2019,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Pellegrino, Roberta},
  title = {A multi-period approach for the optimal energy retrofit planning of street lighting systems},
  year = {2019},
  journal = {Applied Sciences (Switzerland)},
  volume = {9},
  number = {5},
  doi = {10.3390/app9051025},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063660288&doi=10.3390%2fapp9051025&partnerID=40&md5=80ca57851d94e4757320cee529983b5f},
  abstract = {Investing in the optimal measures for improving the energy efficiency of urban street lighting systems has become strategic for the economic, technological and social development of cities. The decision-making process for the selection of the optimal set of interventions is not so straightforward. Several criticalities-such as difficulties getting access to credit for companies involved in street lighting systems refurbishment, budget constraints of municipalities, and unawareness of the actual energy and economic performance after a retrofitting intervention-require a decision-making approach that supports the city energy manager in selecting the optimal street lighting energy efficiency retrofitting solution while looking not only based on the available budget, but also based on the future savings in energy expenditures. In this context, the purpose of our research is to develop an effective decision-making model supporting the optimal multi-period planning of the street lighting energy efficiency retrofitting, which proves to be more effective and beneficial than the classical single-period approach and has never before been applied to the considered public lighting system context. The proposed methodology is applied to a real street lighting system in the city of Bari, Italy, showing the energy savings and financial benefit obtained through the proposed method. Numerical experiments are used to investigate and quantify the effects of using a multi-period planning approach instead of a single-period approach. © 2019 by the authors.},
  author_keywords = {Energy efficiency management; Multi-period planning; Optimization; Street lighting},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11; All Open Access, Gold Open Access, Green Open Access}
  }

• Carli, R. & Dotoli, M. (2019) Decentralized control for residential energy management of a smart users’ microgrid with renewable energy exchange. IN IEEE/CAA Journal of Automatica Sinica, 6.641 – 656. doi:10.1109/JAS.2019.1911462
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a decentralized control strategy for the scheduling of electrical energy activities of a microgrid composed of smart homes connected to a distributor and exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is stated and solved with the aim of reducing the overall energy supply from the grid, by allowing users to exchange the surplus renewable energy and by optimally planning users x02BC controllable loads. We assume that each smart home can both buy x002F sell energy from x002F to the grid taking into account time-varying non-linear pricing signals. Simultaneously, smart homes cooperate and may buy x002F sell locally harvested renewable energy from x002F to other smart homes. The resulting optimization problem is formulated as a non-convex non-linear programming problem with a coupling of decision variables in the constraints. The proposed solution is based on a novel heuristic iterative decentralized scheme algorithm that suitably extends the Alternating Direction Method of Multipliers to a non-convex and decentralized setting. We discuss the conditions that guarantee the convergence of the presented algorithm. Finally, the application of the proposed technique to a case study under several scenarios shows its effectiveness. © 2014 Chinese Association of Automation.

  @ARTICLE{Carli2019641,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Decentralized control for residential energy management of a smart users’ microgrid with renewable energy exchange},
  year = {2019},
  journal = {IEEE/CAA Journal of Automatica Sinica},
  volume = {6},
  number = {3},
  pages = {641 – 656},
  doi = {10.1109/JAS.2019.1911462},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065583902&doi=10.1109%2fJAS.2019.1911462&partnerID=40&md5=dfb517c8f1147f9d27b6d1082a326908},
  abstract = {This paper presents a decentralized control strategy for the scheduling of electrical energy activities of a microgrid composed of smart homes connected to a distributor and exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is stated and solved with the aim of reducing the overall energy supply from the grid, by allowing users to exchange the surplus renewable energy and by optimally planning users x02BC controllable loads. We assume that each smart home can both buy x002F sell energy from x002F to the grid taking into account time-varying non-linear pricing signals. Simultaneously, smart homes cooperate and may buy x002F sell locally harvested renewable energy from x002F to other smart homes. The resulting optimization problem is formulated as a non-convex non-linear programming problem with a coupling of decision variables in the constraints. The proposed solution is based on a novel heuristic iterative decentralized scheme algorithm that suitably extends the Alternating Direction Method of Multipliers to a non-convex and decentralized setting. We discuss the conditions that guarantee the convergence of the presented algorithm. Finally, the application of the proposed technique to a case study under several scenarios shows its effectiveness. © 2014 Chinese Association of Automation.},
  keywords = {Automation; Decentralized control; Energy resources; Heuristic methods; Intelligent buildings; Microgrids; Nonlinear programming; Scheduling; Alternating direction method of multipliers; Decision variables; Distributed Energy Resources; Nonlinear programming problem; Optimization problems; Renewable energies; Residential energy; Scheduling problem; Iterative methods},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 80}
  }

• Othman, S. B., Hammadi, S., Zgaya, H., Renard, J. & Dotoli, M. (2019) Dynamic schedule execution to improve adult emergency department performance in real-time IN 33rd Annual European Simulation and Modelling Conference 2019, ESM 2019., 272 – 278.
  [BibTeX] [Abstract] [Download PDF]

  An Emergency Department (ED) is a very complex system involving heterogeneous patients and several kinds of resources that evolve within a sophisticated process. The management methodology should be chosen in a more effective and targeted way so as to meet the increasing patients’ requirements. Our objective is to find out fast solutions for unscheduled arrivals, dynamic competing priorities and heterogeneous patient care needs. The primary objective of this article is to provide ED managers with internal cost-effective solutions and perceptions in order to reduce overcrowding phenomenon impacts and enhance ED performance. Simulation results show that our scheduling method can significantly reduce the total response time of patients. Copyright © 2019 EUROSIS-ETI.

  @CONFERENCE{Othman2019272,
  author = {Othman, Sarah Ben and Hammadi, Slim and Zgaya, Hayfa and Renard, Jean-Marie and Dotoli, Mariagrazia},
  title = {Dynamic schedule execution to improve adult emergency department performance in real-time},
  year = {2019},
  journal = {33rd Annual European Simulation and Modelling Conference 2019, ESM 2019},
  pages = {272 – 278},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076226919&partnerID=40&md5=f1aa7d4632e0dfd85e1f406b8809d153},
  abstract = {An Emergency Department (ED) is a very complex system involving heterogeneous patients and several kinds of resources that evolve within a sophisticated process. The management methodology should be chosen in a more effective and targeted way so as to meet the increasing patients' requirements. Our objective is to find out fast solutions for unscheduled arrivals, dynamic competing priorities and heterogeneous patient care needs. The primary objective of this article is to provide ED managers with internal cost-effective solutions and perceptions in order to reduce overcrowding phenomenon impacts and enhance ED performance. Simulation results show that our scheduling method can significantly reduce the total response time of patients. Copyright © 2019 EUROSIS-ETI.},
  author_keywords = {Emergency Department; Overcrowding; Response time; Scheduling},
  keywords = {Cost effectiveness; Modal analysis; Response time (computer systems); Scheduling; Dynamic schedule; Emergency departments; Fast solutions; Internal costs; Management methodologies; Overcrowding; Primary objective; Scheduling methods; Emergency rooms},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Carli, R., Cavone, G., Dotoli, M., Epicoco, N. & Scarabaggio, P. (2019) Model predictive control for thermal comfort optimization in building energy management systems IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 2608 – 2613. doi:10.1109/SMC.2019.8914489
  [BibTeX] [Abstract] [Download PDF]

  Model Predictive Control (MPC) has recently gained special attention to efficiently regulate Heating, Ventilation and Air Conditioning (HVAC) systems of buildings, since it explicitly allows energy savings while maintaining thermal comfort criteria. In this paper we propose a MPC algorithm for the on-line optimization of both the indoor thermal comfort and the related energy consumption of buildings. We use Fanger’s Predicted Mean Vote (PMV) as thermal comfort index, while to predict the energy performance of the building, we adopt a simplified thermal model. This allows computing optimal control actions by defining and solving a tractable non-linear optimization problem that incorporates the PMV index into the MPC cost function in addition to a term accounting for energy saving. The proposed MPC approach is implemented on a building automation system deployed in an office building located at the Polytechnic of Bari (Italy). Several on-field tests are performed to assess the applicability and efficacy of the control algorithm in a real environment against classical thermal comfort control approach based on the use of thermostats. © 2019 IEEE.

  @CONFERENCE{Carli20192608,
  author = {Carli, Raffaele and Cavone, Graziana and Dotoli, Mariagrazia and Epicoco, Nicola and Scarabaggio, Paolo},
  title = {Model predictive control for thermal comfort optimization in building energy management systems},
  year = {2019},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {2019-October},
  pages = {2608 – 2613},
  doi = {10.1109/SMC.2019.8914489},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076778873&doi=10.1109%2fSMC.2019.8914489&partnerID=40&md5=3c982fb93adbcfb5202b48b60ad0f22d},
  abstract = {Model Predictive Control (MPC) has recently gained special attention to efficiently regulate Heating, Ventilation and Air Conditioning (HVAC) systems of buildings, since it explicitly allows energy savings while maintaining thermal comfort criteria. In this paper we propose a MPC algorithm for the on-line optimization of both the indoor thermal comfort and the related energy consumption of buildings. We use Fanger's Predicted Mean Vote (PMV) as thermal comfort index, while to predict the energy performance of the building, we adopt a simplified thermal model. This allows computing optimal control actions by defining and solving a tractable non-linear optimization problem that incorporates the PMV index into the MPC cost function in addition to a term accounting for energy saving. The proposed MPC approach is implemented on a building automation system deployed in an office building located at the Polytechnic of Bari (Italy). Several on-field tests are performed to assess the applicability and efficacy of the control algorithm in a real environment against classical thermal comfort control approach based on the use of thermostats. © 2019 IEEE.},
  keywords = {Air conditioning; Automation; Cost functions; Energy conservation; Energy management systems; Energy utilization; Intelligent buildings; Nonlinear programming; Office buildings; Predictive control systems; Thermal comfort; Building automation systems; Energy performance; Indoor thermal comfort; Non-linear optimization problems; Online optimization; Predicted mean vote; Thermal comfort control; Thermal comfort index; Model predictive control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 20}
  }

• Carli, R., Cavone, G., Dotoli, M., Epicoco, N., Manganiello, C. & Tricarico, L. (2019) ICT-based methodologies for sheet metal forming design: A survey on simulation approaches IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 128 – 133. doi:10.1109/SMC.2019.8914082
  [BibTeX] [Abstract] [Download PDF]

  Sheet metal forming processes are widely adopted in manufacturing industries and in the recent years there has been a growing demand for sheet metal items with different shapes and characteristics. However, the traditional process is unable to meet the modern industrial requirements, mainly due to the high costs of dies and the long manufacturing time cycles. On the contrary, developing products with high speed, low cost, and high quality is a key issue. Therefore, new methods and technologies to speed up the sheet metal forming process while keeping costs limited are needed. In particular, a key issue is the proper design of the forming process, which can benefit from the use of Information and Communications Technology (ICT) simulation techniques. This paper investigates the recent trends on ICT-based methodologies for sheet metal forming to identify the foremost research areas whose advancement will lead meeting the modern market’s needs. © 2019 IEEE.

  @CONFERENCE{Carli2019128,
  author = {Carli, Raffaele and Cavone, Graziana and Dotoli, Mariagrazia and Epicoco, Nicola and Manganiello, Claudio and Tricarico, Luigi},
  title = {ICT-based methodologies for sheet metal forming design: A survey on simulation approaches},
  year = {2019},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {2019-October},
  pages = {128 – 133},
  doi = {10.1109/SMC.2019.8914082},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076787727&doi=10.1109%2fSMC.2019.8914082&partnerID=40&md5=b067223578db03937c9be68febc5f920},
  abstract = {Sheet metal forming processes are widely adopted in manufacturing industries and in the recent years there has been a growing demand for sheet metal items with different shapes and characteristics. However, the traditional process is unable to meet the modern industrial requirements, mainly due to the high costs of dies and the long manufacturing time cycles. On the contrary, developing products with high speed, low cost, and high quality is a key issue. Therefore, new methods and technologies to speed up the sheet metal forming process while keeping costs limited are needed. In particular, a key issue is the proper design of the forming process, which can benefit from the use of Information and Communications Technology (ICT) simulation techniques. This paper investigates the recent trends on ICT-based methodologies for sheet metal forming to identify the foremost research areas whose advancement will lead meeting the modern market's needs. © 2019 IEEE.},
  keywords = {Costs; Information use; Metal forming; Metals; Developing product; Different shapes; Industrial requirements; Information and communications technology; Manufacturing industries; Manufacturing time; Simulation approach; Simulation technique; Sheet metal},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Hosseini, S. M., Carli, R. & Dotoli, M. (2019) Robust energy scheduling of interconnected smart homes with shared energy storage under quadratic pricing IN IEEE International Conference on Automation Science and Engineering., 966 – 971. doi:10.1109/COASE.2019.8843230
  [BibTeX] [Abstract] [Download PDF]

  In this paper, we propose a novel robust framework for day-ahead energy scheduling of interconnected smart homes with shared energy storage system (ESS), taking into account users’ behavior uncertainty. The objective is minimizing the total energy payment for each user while satisfying the constraint on the feasibility of energy transactions between users and the power grid in presence of data uncertainty. Unlike most existing robust scheduling frameworks that assume a linear cost function for energy purchased from the grid, our design presents a tractable robust optimization scheme to solve the energy scheduling problem with a more realistic quadratic cost function. We model device/comfort constraints as well as contractual obligations imposed by the power grid restricting the users’ energy consumption to a maximum level at each time slot. Thus, in our problem, uncertainty affects both the quadratic objective function and linear contractual constraints. To solve the resulting problem, we first formulate a deterministic model of the scheduling problem, then establish a min-max robust counterpart, and finally apply some mathematical transformations to solve the equivalent problem. We also deal with the conservatism of the robust control algorithm and flexibility of the method for application to different settings. The validity and effectiveness of the proposed approach is verified by simulation results. © 2019 IEEE.

  @CONFERENCE{Hosseini2019966,
  author = {Hosseini, Seyed Mohsen and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Robust energy scheduling of interconnected smart homes with shared energy storage under quadratic pricing},
  year = {2019},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2019-August},
  pages = {966 – 971},
  doi = {10.1109/COASE.2019.8843230},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072987292&doi=10.1109%2fCOASE.2019.8843230&partnerID=40&md5=6989d41f45c9a005b8a3dd9ebcf6bbfd},
  abstract = {In this paper, we propose a novel robust framework for day-ahead energy scheduling of interconnected smart homes with shared energy storage system (ESS), taking into account users' behavior uncertainty. The objective is minimizing the total energy payment for each user while satisfying the constraint on the feasibility of energy transactions between users and the power grid in presence of data uncertainty. Unlike most existing robust scheduling frameworks that assume a linear cost function for energy purchased from the grid, our design presents a tractable robust optimization scheme to solve the energy scheduling problem with a more realistic quadratic cost function. We model device/comfort constraints as well as contractual obligations imposed by the power grid restricting the users' energy consumption to a maximum level at each time slot. Thus, in our problem, uncertainty affects both the quadratic objective function and linear contractual constraints. To solve the resulting problem, we first formulate a deterministic model of the scheduling problem, then establish a min-max robust counterpart, and finally apply some mathematical transformations to solve the equivalent problem. We also deal with the conservatism of the robust control algorithm and flexibility of the method for application to different settings. The validity and effectiveness of the proposed approach is verified by simulation results. © 2019 IEEE.},
  keywords = {Automation; Cost functions; Digital storage; Electric power transmission networks; Energy storage; Energy utilization; Intelligent buildings; Mathematical transformations; Optimization; Robust control; Scheduling; Contractual obligations; Deterministic modeling; Energy storage systems; Linear cost functions; Quadratic cost functions; Quadratic objective functions; Robust optimization; Scheduling problem; Costs},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Dotoli, M., Fay, A., Miśkowicz, M. & Seatzu, C. (2019) An overview of current technologies and emerging trends in factory automation. IN International Journal of Production Research, 57.5047 – 5067. doi:10.1080/00207543.2018.1510558
  [BibTeX] [Abstract] [Download PDF]

  In this paper we provide an overview of recent theoretical approaches and technologies that respond to the fundamental challenges of modern factory automation. We classify these major methods and technologies into several groups and, for seven of them – namely: vertical integration of factory automation systems; distributed and decentralised control, smart sensors and actuators in factories; networked control systems and wireless sensors and actuators; autonomy and self-organisation of factories; advanced sensing for factory automation; semantic models of factories; engineering methods of factory automation systems – we report recent research contributions and formulate open technical problems in the domain of modern factory automation. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

  @ARTICLE{Dotoli20195047,
  author = {Dotoli, Mariagrazia and Fay, Alexander and Miśkowicz, Marek and Seatzu, Carla},
  title = {An overview of current technologies and emerging trends in factory automation},
  year = {2019},
  journal = {International Journal of Production Research},
  volume = {57},
  number = {15-16},
  pages = {5047 – 5067},
  doi = {10.1080/00207543.2018.1510558},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052118672&doi=10.1080%2f00207543.2018.1510558&partnerID=40&md5=ea5b29c60f57c7cfeb39ace72401c504},
  abstract = {In this paper we provide an overview of recent theoretical approaches and technologies that respond to the fundamental challenges of modern factory automation. We classify these major methods and technologies into several groups and, for seven of them - namely: vertical integration of factory automation systems; distributed and decentralised control, smart sensors and actuators in factories; networked control systems and wireless sensors and actuators; autonomy and self-organisation of factories; advanced sensing for factory automation; semantic models of factories; engineering methods of factory automation systems - we report recent research contributions and formulate open technical problems in the domain of modern factory automation. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.},
  author_keywords = {advanced sensing; autonomous systems; decentralised control; distributed control; engineering methods; factory automation; manufacturing systems; networked control systems; self-organisation; semantic models; smart sensors and actuators; vertical integration; wireless sensor networks},
  keywords = {Actuators; Decentralized control; Distributed parameter control systems; Factory automation; Manufacture; Semantics; Smart sensors; Wireless sensor networks; advanced sensing; Autonomous systems; Decentralised control; Distributed control; Engineering methods; Self organisation; Semantic Model; Sensors and actuators; Vertical integration; Networked control systems},
  type = {Review},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 80}
  }

2018

• Cavone, G., Dotoli, M., Epicoco, N., Franceschelli, M. & Seatzu, C. (2018) Hybrid Petri Nets to Re-design Low-Automated Production Processes: the Case Study of a Sardinian Bakery , 265 – 270. doi:10.1016/j.ifacol.2018.06.311
  [BibTeX] [Abstract] [Download PDF]

  This paper shows the practical relevance of first-order hybrid Petri nets in the re-design process of low-automated production systems. In particular, we analyze the case study of a bakery producing “pane Carasau” a typical Sardinian bread, whose traditional production plant currently has difficulties in coping with the constant increase in market demand. Through first-order hybrid Petri nets, the current functioning and the operating features and dynamics of the case study are modelled, waste sources and bottlenecks are detected, and alternative re-designed scenarios are implemented and evaluated to identify the most suitable reengineering actions to be developed. © 2018

  @CONFERENCE{Cavone2018265,
  author = {Cavone, G. and Dotoli, M. and Epicoco, N. and Franceschelli, M. and Seatzu, C.},
  title = {Hybrid Petri Nets to Re-design Low-Automated Production Processes: the Case Study of a Sardinian Bakery},
  year = {2018},
  volume = {51},
  number = {7},
  pages = {265 – 270},
  doi = {10.1016/j.ifacol.2018.06.311},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050128384&doi=10.1016%2fj.ifacol.2018.06.311&partnerID=40&md5=832573ffac1f56c0f884bc55c52b23d1},
  abstract = {This paper shows the practical relevance of first-order hybrid Petri nets in the re-design process of low-automated production systems. In particular, we analyze the case study of a bakery producing “pane Carasau” a typical Sardinian bread, whose traditional production plant currently has difficulties in coping with the constant increase in market demand. Through first-order hybrid Petri nets, the current functioning and the operating features and dynamics of the case study are modelled, waste sources and bottlenecks are detected, and alternative re-designed scenarios are implemented and evaluated to identify the most suitable reengineering actions to be developed. © 2018},
  author_keywords = {First-Order Hybrid Petri nets; Production processes; Re-design; Reengineering},
  keywords = {Bakeries; Design; Reengineering; Automated production systems; Automated productions; Design process; First-order hybrid Petri nets; Hybrid Petri net; Market demand; Production plant; Production process; Petri nets},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 20; All Open Access, Gold Open Access}
  }

• Cavone, G., Dotoli, M., Epicoco, N. & Seatzu, C. (2018) Efficient Resource Planning of Intermodal Terminals under Uncertainty , 398 – 403. doi:10.1016/j.ifacol.2018.07.065
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a decision support tool for the efficient resource planning and management of intermodal terminals under uncertainty, allowing to address the planning issue under imprecise or uncertain data (e.g., estimates on flows, resource utilization, operating conditions). The procedure consists of three steps: 1) the definition of a Timed Petri Net model of the terminal; 2) the computation of suitable performance indices to evaluate whether the current configuration is able to cope with a foreseen increase in the freight flows; 3) in the case of not satisfactory values of the indices at the previous step, the simulation of alternative planning solutions and the detection of the most efficient one via a cross-efficiency fuzzy Data Envelopment Analysis technique. In order to test its effectiveness, the procedure is applied to a real case study. © 2018

  @CONFERENCE{Cavone2018398,
  author = {Cavone, Graziana and Dotoli, Mariagrazia and Epicoco, Nicola and Seatzu, Carla},
  title = {Efficient Resource Planning of Intermodal Terminals under Uncertainty},
  year = {2018},
  volume = {51},
  number = {9},
  pages = {398 – 403},
  doi = {10.1016/j.ifacol.2018.07.065},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050140566&doi=10.1016%2fj.ifacol.2018.07.065&partnerID=40&md5=edaa20f412201b8f7e7839c4fc246aad},
  abstract = {This paper presents a decision support tool for the efficient resource planning and management of intermodal terminals under uncertainty, allowing to address the planning issue under imprecise or uncertain data (e.g., estimates on flows, resource utilization, operating conditions). The procedure consists of three steps: 1) the definition of a Timed Petri Net model of the terminal; 2) the computation of suitable performance indices to evaluate whether the current configuration is able to cope with a foreseen increase in the freight flows; 3) in the case of not satisfactory values of the indices at the previous step, the simulation of alternative planning solutions and the detection of the most efficient one via a cross-efficiency fuzzy Data Envelopment Analysis technique. In order to test its effectiveness, the procedure is applied to a real case study. © 2018},
  author_keywords = {Data Envelopment Analysis; efficiency; fuzzy theory; intermodal terminals; performance evaluation; Petri Nets; resource planning; uncertainty},
  keywords = {Computation theory; Data envelopment analysis; Decision support systems; Efficiency; Petri nets; Resource allocation; Uncertainty analysis; Fuzzy theory; Intermodal terminals; performance evaluation; Resource planning; uncertainty; Information management},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6; All Open Access, Gold Open Access}
  }

• Carli, R., Dotoli, M. & Pellegrino, R. (2018) A decision-making tool for energy efficiency optimization of street lighting. IN Computers and Operations Research, 96.223 – 235. doi:10.1016/j.cor.2017.11.016
  [BibTeX] [Abstract] [Download PDF]

  This paper develops a multi-criteria decision making tool to support the public decision maker in optimizing energy retrofit interventions on existing public street lighting systems. The related literature analysis clearly highlights that, to date, only a few number of studies deal with the definition of optimal decision strategies complying with multiple and conflicting objectives in the planning of street lighting refurbishment. To fill this gap, we propose a decision making tool that allows deciding, in an integrated way, the optimal energy retrofit plan in order to simultaneously reduce energy consumption, maintain comfort, protect the environment, and optimize the distribution of actions in subsystems, while ensuring an efficient use of public funds. The presented tool is applied to a real street lighting system of a wide urban area in Bari, Italy. The obtained results highlight that the approach effectively supports the city energy manager in the refurbishment of the street lighting systems. © 2017 Elsevier Ltd

  @ARTICLE{Carli2018223,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Pellegrino, Roberta},
  title = {A decision-making tool for energy efficiency optimization of street lighting},
  year = {2018},
  journal = {Computers and Operations Research},
  volume = {96},
  pages = {223 – 235},
  doi = {10.1016/j.cor.2017.11.016},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044511260&doi=10.1016%2fj.cor.2017.11.016&partnerID=40&md5=f655fabb0054cefa3a05bcc0c63059f4},
  abstract = {This paper develops a multi-criteria decision making tool to support the public decision maker in optimizing energy retrofit interventions on existing public street lighting systems. The related literature analysis clearly highlights that, to date, only a few number of studies deal with the definition of optimal decision strategies complying with multiple and conflicting objectives in the planning of street lighting refurbishment. To fill this gap, we propose a decision making tool that allows deciding, in an integrated way, the optimal energy retrofit plan in order to simultaneously reduce energy consumption, maintain comfort, protect the environment, and optimize the distribution of actions in subsystems, while ensuring an efficient use of public funds. The presented tool is applied to a real street lighting system of a wide urban area in Bari, Italy. The obtained results highlight that the approach effectively supports the city energy manager in the refurbishment of the street lighting systems. © 2017 Elsevier Ltd},
  author_keywords = {Energy efficiency management; Multi-criteria optimization; Public street lighting},
  keywords = {Decision making; Energy utilization; Lighting fixtures; Multiobjective optimization; Retrofitting; Street lighting; Urban planning; Conflicting objectives; Efficiency managements; Energy efficiency optimizations; Multi criteria decision making; Multicriteria optimization; Optimal decision strategy; Reduce energy consumption; Street lighting system; Energy efficiency},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 70}
  }

• Carli, R. & Dotoli, M. (2018) A Distributed Control Algorithm for Optimal Charging of Electric Vehicle Fleets with Congestion Management , 373 – 378. doi:10.1016/j.ifacol.2018.07.061
  [BibTeX] [Abstract] [Download PDF]

  This paper proposes a novel distributed control strategy for the optimal charging of a fleet of Electric Vehicles (EVs) in case of limited overall capacity of the electrical distribution network. The optimal charging is obtained as the solution of a scheduling problem aiming at a cost-optimal profile of the aggregated energy demand. The resulting optimization problem is formulated as a quadratic programming problem with a coupling of decision variables both in the objective function and in the constraint. We assume a minimal information structure, where users locally communicate only with their neighbors, without relying on a central decision maker. The solution approach relies on an iterative distributed algorithm based on duality, proximity, and consensus theory. A simulated case study demonstrates that the approach allows achieving the global optimum. © 2018

  @CONFERENCE{Carli2018373,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A Distributed Control Algorithm for Optimal Charging of Electric Vehicle Fleets with Congestion Management},
  year = {2018},
  volume = {51},
  number = {9},
  pages = {373 – 378},
  doi = {10.1016/j.ifacol.2018.07.061},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050093123&doi=10.1016%2fj.ifacol.2018.07.061&partnerID=40&md5=87f63aa0bd1f3aa33b573169b8a48e32},
  abstract = {This paper proposes a novel distributed control strategy for the optimal charging of a fleet of Electric Vehicles (EVs) in case of limited overall capacity of the electrical distribution network. The optimal charging is obtained as the solution of a scheduling problem aiming at a cost-optimal profile of the aggregated energy demand. The resulting optimization problem is formulated as a quadratic programming problem with a coupling of decision variables both in the objective function and in the constraint. We assume a minimal information structure, where users locally communicate only with their neighbors, without relying on a central decision maker. The solution approach relies on an iterative distributed algorithm based on duality, proximity, and consensus theory. A simulated case study demonstrates that the approach allows achieving the global optimum. © 2018},
  author_keywords = {Decentralized; Distributed Control; Electric Vehicles; Large scale optimization problems; Scheduling algorithms},
  keywords = {Charging (batteries); Decision making; Electric vehicles; Fleet operations; Iterative methods; Quadratic programming; Scheduling algorithms; Decentralized; Distributed control; Distributed control algorithms; Distributed control strategy; Electric Vehicles (EVs); Electrical distribution networks; Large-scale optimization; Quadratic programming problems; Traffic congestion},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 37; All Open Access, Gold Open Access}
  }

• Hosseini, S. M., Carli, R. & Dotoli, M. (2018) Model Predictive Control for Real-Time Residential Energy Scheduling under Uncertainties IN Proceedings – 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018., 1386 – 1391. doi:10.1109/SMC.2018.00242
  [BibTeX] [Abstract] [Download PDF]

  This paper proposes a real-time strategy based on Model Predictive Control (MPC) for the energy scheduling of a grid-connected smart residential user equipped with deferrable and non-deferrable electrical appliances, a renewable energy source (RES), and an electrical energy storage system (EESS). The proposed control scheme relies on an iterative finite horizon on-line optimization, implementing a quadratic cost function to minimize the electricity bill of the user’s load demand and to limit the peak-to-average ratio (PAR) of the energy consumption profile whilst considering operational constraints. At each time step, the optimization problem is solved providing the cost-optimal energy consumption profile for the user’s deferrable loads and the optimal charging/discharging profile for the EESS, taking into account forecast uncertainties by using the most updated predicted values of local RES generation and non-deferrable loads consumption. The performance and effectiveness of the proposed framework are evaluated for a case study where the dynamics of the considered residential energy system is simulated under uncertainties both in the forecast of the RES generation and the non-deferrable loads energy consumption. © 2018 IEEE.

  @CONFERENCE{Hosseini20181386,
  author = {Hosseini, Seyed Mohsen and Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Model Predictive Control for Real-Time Residential Energy Scheduling under Uncertainties},
  year = {2018},
  journal = {Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018},
  pages = {1386 – 1391},
  doi = {10.1109/SMC.2018.00242},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062230383&doi=10.1109%2fSMC.2018.00242&partnerID=40&md5=2f024e90b4a067ff3c318f9e0a035f00},
  abstract = {This paper proposes a real-time strategy based on Model Predictive Control (MPC) for the energy scheduling of a grid-connected smart residential user equipped with deferrable and non-deferrable electrical appliances, a renewable energy source (RES), and an electrical energy storage system (EESS). The proposed control scheme relies on an iterative finite horizon on-line optimization, implementing a quadratic cost function to minimize the electricity bill of the user's load demand and to limit the peak-to-average ratio (PAR) of the energy consumption profile whilst considering operational constraints. At each time step, the optimization problem is solved providing the cost-optimal energy consumption profile for the user's deferrable loads and the optimal charging/discharging profile for the EESS, taking into account forecast uncertainties by using the most updated predicted values of local RES generation and non-deferrable loads consumption. The performance and effectiveness of the proposed framework are evaluated for a case study where the dynamics of the considered residential energy system is simulated under uncertainties both in the forecast of the RES generation and the non-deferrable loads energy consumption. © 2018 IEEE.},
  author_keywords = {energy scheduling; model predictive control (MPC); residential energy management; uncertainties},
  keywords = {Cost functions; Electric energy storage; Energy utilization; Housing; Predictive control systems; Renewable energy resources; Scheduling; Electrical energy storage systems; Energy; Energy scheduling; Energy-consumption; Model predictive control; Model-predictive control; Renewable energy source; Residential energy; Residential energy management; Uncertainty; Model predictive control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 31}
  }

• Carli, R., Dotoli, M. & Epicoco, N. (2018) Cost-Optimal Energy Scheduling of a Smart Home under Uncertainty IN 2018 IEEE Conference on Control Technology and Applications, CCTA 2018., 1668 – 1673. doi:10.1109/CCTA.2018.8511345
  [BibTeX] [Abstract] [Download PDF]

  We present a novel energy scheduling approach under uncertain data for smart homes taking into account the presence of controllable electrical loads, renewable energy sources, dispatchable energy generators, and energy storage systems. The problem is stated as a fuzzy linear programming and is aimed at minimizing energy costs. The proposed approach allows managing the use of electrical devices, plan the energy production and supplying, and program the storage charging and discharging profiles under uncertain data. The method is validated through a literature case study showing its effectiveness in exploiting the potential of local energy generation and storage and in reducing the energy consumption costs, while limiting the peak average ratio of the energy profiles and complying with the user’s energy needs. © 2018 IEEE.

  @CONFERENCE{Carli20181668,
  author = {Carli, R. and Dotoli, M. and Epicoco, N.},
  title = {Cost-Optimal Energy Scheduling of a Smart Home under Uncertainty},
  year = {2018},
  journal = {2018 IEEE Conference on Control Technology and Applications, CCTA 2018},
  pages = {1668 – 1673},
  doi = {10.1109/CCTA.2018.8511345},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056899368&doi=10.1109%2fCCTA.2018.8511345&partnerID=40&md5=df2f65f9300879823bcc53a5aada2f14},
  abstract = {We present a novel energy scheduling approach under uncertain data for smart homes taking into account the presence of controllable electrical loads, renewable energy sources, dispatchable energy generators, and energy storage systems. The problem is stated as a fuzzy linear programming and is aimed at minimizing energy costs. The proposed approach allows managing the use of electrical devices, plan the energy production and supplying, and program the storage charging and discharging profiles under uncertain data. The method is validated through a literature case study showing its effectiveness in exploiting the potential of local energy generation and storage and in reducing the energy consumption costs, while limiting the peak average ratio of the energy profiles and complying with the user's energy needs. © 2018 IEEE.},
  keywords = {Automation; Energy utilization; Intelligent buildings; Linear programming; Renewable energy resources; Scheduling; Dispatchable energies; Electrical devices; Electrical load; Energy productions; Energy storage systems; Fuzzy linear programming; Minimizing energy; Renewable energy source; Digital storage},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Cavone, G., Dotoli, M., Epicoco, N., Morelli, D. & Seatzu, C. (2018) A Game-theoretical Design Technique for Multi-stage Supply Chains under Uncertainty IN IEEE International Conference on Automation Science and Engineering., 528 – 533. doi:10.1109/COASE.2018.8560501
  [BibTeX] [Abstract] [Download PDF]

  We present a design approach for multi-stage Supply Chains (SCs) that allows selecting candidates and assigning them orders under uncertainty. A bargaining game model in its extensive form (i.e., with a time sequencing of moves) and in a fuzzy setting is proposed. The product quantities that each actor requires from the previous SC stage are determined modelling the real behavior of SC stakeholders, which on the one hand act to maximize their own profit, on the other hand cooperate to maximize the overall efficiency of the SC and minimize production costs and lead times. Assignments are determined taking into account stock levels, uncertain production or warehouse capacities, and customers’ demand. Thus, the method supports the decision making process providing an agile, cooperative, and resource-efficient design of multi-stage SCs under uncertain parameters. A literature SC is used as a test case to evaluate the effectiveness of the technique. © 2018 IEEE.

  @CONFERENCE{Cavone2018528,
  author = {Cavone, Graziana and Dotoli, Mariagrazia and Epicoco, Nicola and Morelli, Davide and Seatzu, Carla},
  title = {A Game-theoretical Design Technique for Multi-stage Supply Chains under Uncertainty},
  year = {2018},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2018-August},
  pages = {528 – 533},
  doi = {10.1109/COASE.2018.8560501},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059976158&doi=10.1109%2fCOASE.2018.8560501&partnerID=40&md5=029376a062b0c55a7cccfc170988ada1},
  abstract = {We present a design approach for multi-stage Supply Chains (SCs) that allows selecting candidates and assigning them orders under uncertainty. A bargaining game model in its extensive form (i.e., with a time sequencing of moves) and in a fuzzy setting is proposed. The product quantities that each actor requires from the previous SC stage are determined modelling the real behavior of SC stakeholders, which on the one hand act to maximize their own profit, on the other hand cooperate to maximize the overall efficiency of the SC and minimize production costs and lead times. Assignments are determined taking into account stock levels, uncertain production or warehouse capacities, and customers' demand. Thus, the method supports the decision making process providing an agile, cooperative, and resource-efficient design of multi-stage SCs under uncertain parameters. A literature SC is used as a test case to evaluate the effectiveness of the technique. © 2018 IEEE.},
  keywords = {Decision making; Supply chains; Uncertainty analysis; Bargaining game; Decision making process; Design approaches; Overall efficiency; Resource-efficient; Theoretical design; Uncertain parameters; Warehouse capacity; Game theory},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Carli, R., Dotoli, M. & Epicoco, N. (2018) Monitoring traffic congestion in urban areas through probe vehicles: A case study analysis. IN Internet Technology Letters, 1.. doi:10.1002/ITL2.5
  [BibTeX] [Abstract] [Download PDF]

  We present a probe vehicles approach to evaluate traffic congestion in urban areas. The method is illustrated by a real case study in Bari, Italy. Global Positioning System (GPS) data generated by buses are transmitted via General Packet Radio Service (GPRS) to a control station, where they are used to analyze traffic conditions. Traffic indices are evaluated to provide an exhaustive view of roads congestion and imple-ment suitable control strategies. Thus, traffic administrators can efficiently manage sustainable mobility in cities and people can acquire awareness on traffic and public transport performance. © 2017 John Wiley & Sons, Ltd.

  @ARTICLE{Carli2018,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Epicoco, Nicola},
  title = {Monitoring traffic congestion in urban areas through probe vehicles: A case study analysis},
  year = {2018},
  journal = {Internet Technology Letters},
  volume = {1},
  number = {4},
  doi = {10.1002/ITL2.5},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067574084&doi=10.1002%2fITL2.5&partnerID=40&md5=ca6e723b32a9bcef3ba73f175d805843},
  abstract = {We present a probe vehicles approach to evaluate traffic congestion in urban areas. The method is illustrated by a real case study in Bari, Italy. Global Positioning System (GPS) data generated by buses are transmitted via General Packet Radio Service (GPRS) to a control station, where they are used to analyze traffic conditions. Traffic indices are evaluated to provide an exhaustive view of roads congestion and imple-ment suitable control strategies. Thus, traffic administrators can efficiently manage sustainable mobility in cities and people can acquire awareness on traffic and public transport performance. © 2017 John Wiley & Sons, Ltd.},
  author_keywords = {bus as a probe; traffic monitoring; vehicles to internet},
  type = {Letter},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11; All Open Access, Bronze Open Access}
  }

• Carli, R. & Dotoli, M. (2018) A Decentralized Control Strategy for the Energy Management of Smart Homes with Renewable Energy Exchange IN 2018 IEEE Conference on Control Technology and Applications, CCTA 2018., 1662 – 1667. doi:10.1109/CCTA.2018.8511617
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a decentralized control strategy for the scheduling of energy activities of interconnected smart homes that purchase energy from a supplier while exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is solved with a twofold design objective. First, the model aims at reducing the overall energy supply from the grid, by allowing users to borrow/lend some amount of renewable energy from/to other users. Second, the problem is formulated to optimally plan users’ controllable loads. We assume a time-varying quadratic pricing of the energy purchased from the distribution network. The proposed solution is based on a decentralized optimization algorithm combining parametric optimization with the proximal Jacobian Alternating Direction Method of Multipliers. The application of the proposed technique to a simulated case study under several scenarios shows its effectiveness. © 2018 IEEE.

  @CONFERENCE{Carli20181662,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A Decentralized Control Strategy for the Energy Management of Smart Homes with Renewable Energy Exchange},
  year = {2018},
  journal = {2018 IEEE Conference on Control Technology and Applications, CCTA 2018},
  pages = {1662 – 1667},
  doi = {10.1109/CCTA.2018.8511617},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056821403&doi=10.1109%2fCCTA.2018.8511617&partnerID=40&md5=85a9dde2ca8fa544e4b4a5901580188f},
  abstract = {This paper presents a decentralized control strategy for the scheduling of energy activities of interconnected smart homes that purchase energy from a supplier while exchanging renewable energy produced by individually owned distributed energy resources. The scheduling problem is solved with a twofold design objective. First, the model aims at reducing the overall energy supply from the grid, by allowing users to borrow/lend some amount of renewable energy from/to other users. Second, the problem is formulated to optimally plan users' controllable loads. We assume a time-varying quadratic pricing of the energy purchased from the distribution network. The proposed solution is based on a decentralized optimization algorithm combining parametric optimization with the proximal Jacobian Alternating Direction Method of Multipliers. The application of the proposed technique to a simulated case study under several scenarios shows its effectiveness. © 2018 IEEE.},
  keywords = {Automation; Energy resources; Intelligent buildings; Scheduling; Alternating direction method of multipliers; Controllable loads; Decentralized optimization; Design objectives; Distributed Energy Resources; Parametric optimization; Renewable energies; Scheduling problem; Decentralized control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 4}
  }

• Cavone, G., Dotoli, M. & Seatzu, C. (2018) A Survey on Petri Net Models for Freight Logistics and Transportation Systems. IN IEEE Transactions on Intelligent Transportation Systems, 19.1795 – 1813. doi:10.1109/TITS.2017.2737788
  [BibTeX] [Abstract] [Download PDF]

  The benefits of logistics and transportation systems to citizens, economy, and society can strongly increase when considering a smart, safe, and environmentally friendly management. This results in the implementation of intelligent transportation systems that combine innovative technologies and transportation frameworks at the aim of finding proper solutions to the related decision problems. To achieve such a goal, the intrinsic discrete event dynamics of these systems should be considered when deriving a model to be used for simulation, analysis, optimization, and control. Among the different discrete event models, Petri Nets (PNs) are particularly effective due to a series of relevant features. In addition, several high-level PN models (e.g., colored, continuous, or hybrid) allow the solution of complex and large-dimension problems that typically arise from real-life applications in the area of freight logistics and transportation systems. This paper presents a survey on contributions in this area. Papers are classified according to the addressed problem, namely, strategic/tactical or operational decision-making-level problem, and the adopted PN formalism. We also debate the approaches’ viability, discussing contributions and limitations, and identify future research directions to enhance the successful application of PNs in freight logistics and transportation systems. © 2000-2011 IEEE.

  @ARTICLE{Cavone20181795,
  author = {Cavone, Graziana and Dotoli, Mariagrazia and Seatzu, Carla},
  title = {A Survey on Petri Net Models for Freight Logistics and Transportation Systems},
  year = {2018},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
  volume = {19},
  number = {6},
  pages = {1795 – 1813},
  doi = {10.1109/TITS.2017.2737788},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029185229&doi=10.1109%2fTITS.2017.2737788&partnerID=40&md5=b13acc8aca9a368189e296cec63c8a37},
  abstract = {The benefits of logistics and transportation systems to citizens, economy, and society can strongly increase when considering a smart, safe, and environmentally friendly management. This results in the implementation of intelligent transportation systems that combine innovative technologies and transportation frameworks at the aim of finding proper solutions to the related decision problems. To achieve such a goal, the intrinsic discrete event dynamics of these systems should be considered when deriving a model to be used for simulation, analysis, optimization, and control. Among the different discrete event models, Petri Nets (PNs) are particularly effective due to a series of relevant features. In addition, several high-level PN models (e.g., colored, continuous, or hybrid) allow the solution of complex and large-dimension problems that typically arise from real-life applications in the area of freight logistics and transportation systems. This paper presents a survey on contributions in this area. Papers are classified according to the addressed problem, namely, strategic/tactical or operational decision-making-level problem, and the adopted PN formalism. We also debate the approaches' viability, discussing contributions and limitations, and identify future research directions to enhance the successful application of PNs in freight logistics and transportation systems. © 2000-2011 IEEE.},
  author_keywords = {control; Freight transportation; management; modeling and simulation; optimization; Petri nets},
  keywords = {Analytical models; Containers; Control engineering; Decision making; Discrete event simulation; Intelligent systems; Logistics; Management; Optimization; Petri nets; Random processes; Stochastic models; Stochastic systems; Surveys; Transportation; Discrete event dynamics; Future research directions; Intelligent transportation systems; Logistics and transportations; Model and simulation; Object oriented model; Operational decision making; Real-life applications; Freight transportation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 58}
  }

• Carli, R. & Dotoli, M. (2018) Distributed Control for Waterfilling of Networked Control Systems with Coupling Constraints IN Proceedings of the IEEE Conference on Decision and Control., 3710 – 3715. doi:10.1109/CDC.2018.8619425
  [BibTeX] [Abstract] [Download PDF]

  In this paper we present a distributed control approach for the multi-user multi-constrained waterfilling. This a specific category of distributed optimization for Networked Control Systems (NCSs), where agents aim at optimizing a non-separable global objective function while satisfying both local constraints and coupling constraints. Differently from the existing literature, in the considered setting we adopt a fully distributed mechanism where communication is allowed between neighbors only. First, we formulate a general multi-user waterfilling-structured optimization problem including coupling constraints, which may represent many engineering distributed control problems. Successively, we define a low-complexity iterative distributed algorithm based on duality, consensus and fixed point mapping theory. Finally, applying the technique to a simulated case referring to the electric vehicles optimal charging problem, we show its effectiveness. © 2018 IEEE.

  @CONFERENCE{Carli20183710,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Distributed Control for Waterfilling of Networked Control Systems with Coupling Constraints},
  year = {2018},
  journal = {Proceedings of the IEEE Conference on Decision and Control},
  volume = {2018-December},
  pages = {3710 – 3715},
  doi = {10.1109/CDC.2018.8619425},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062189943&doi=10.1109%2fCDC.2018.8619425&partnerID=40&md5=3dfd050026baf187539419a0a975db57},
  abstract = {In this paper we present a distributed control approach for the multi-user multi-constrained waterfilling. This a specific category of distributed optimization for Networked Control Systems (NCSs), where agents aim at optimizing a non-separable global objective function while satisfying both local constraints and coupling constraints. Differently from the existing literature, in the considered setting we adopt a fully distributed mechanism where communication is allowed between neighbors only. First, we formulate a general multi-user waterfilling-structured optimization problem including coupling constraints, which may represent many engineering distributed control problems. Successively, we define a low-complexity iterative distributed algorithm based on duality, consensus and fixed point mapping theory. Finally, applying the technique to a simulated case referring to the electric vehicles optimal charging problem, we show its effectiveness. © 2018 IEEE.},
  keywords = {Computational complexity; Distributed parameter control systems; Iterative methods; Coupling constraints; Distributed control; Distributed control problems; Distributed optimization; Global objective functions; Local constraints; Networked Control Systems (NCSs); Structured optimization problem; Networked control systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 4}
  }

• Carli, R., Dotoli, M. & Pellegrino, R. (2018) Multi-criteria decision-making for sustainable metropolitan cities assessment. IN Journal of Environmental Management, 226.46 – 61. doi:10.1016/j.jenvman.2018.07.075
  [BibTeX] [Abstract] [Download PDF]

  The recent development of metropolitan cities, especially in Europe, requires an effective integrated management of city services, infrastructure, and communication networks at a metropolitan level. A preliminary step towards a proper organizational and management strategy of the metropolitan city is the analysis, benchmarking and optimization of the metropolitan areas through a set of indicators coherent with the overall sustainability objective of the metropolitan city. This paper proposes the use of the Analytic Hierarchy Process multi-criteria decision making technique for application in the smart metropolitan city context, with the aim of analysing the sustainable development of energy, water and environmental systems, through a set of objective performance indicators. Specifically, the 35 indicators defined for the Sustainable Development of Energy, Water and Environment Systems Index framework are used. The application of the approach to the real case study of four metropolitan areas (Bari, Bitonto, Mola, and Molfetta) in the city of Bari (Italy) shows its usefulness for the local government in benchmarking metropolitan areas and providing decision indications on how to formulate the sustainable development strategy of the metropolitan city. Based on the Analytic Hierarchy Process characteristics, the results highlight that although one specific area (Mola in the considered case) is globally ranked at the first place, it is only ranked first with respect to some dimensions. Such a result has strong implications for the metropolitan city’s manager who has the possibility to identify and implement targeted actions, which may be designed ad hoc to improve specific dimensions based on the current state of the city, thus maximizing the efficiency and effectiveness of the actions undertaken for the sustainable development of energy, water and environmental systems of the whole metropolitan city. © 2018 Elsevier Ltd

  @ARTICLE{Carli201846,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Pellegrino, Roberta},
  title = {Multi-criteria decision-making for sustainable metropolitan cities assessment},
  year = {2018},
  journal = {Journal of Environmental Management},
  volume = {226},
  pages = {46 – 61},
  doi = {10.1016/j.jenvman.2018.07.075},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051362383&doi=10.1016%2fj.jenvman.2018.07.075&partnerID=40&md5=57606eb68995a362a44497e2b3089e36},
  abstract = {The recent development of metropolitan cities, especially in Europe, requires an effective integrated management of city services, infrastructure, and communication networks at a metropolitan level. A preliminary step towards a proper organizational and management strategy of the metropolitan city is the analysis, benchmarking and optimization of the metropolitan areas through a set of indicators coherent with the overall sustainability objective of the metropolitan city. This paper proposes the use of the Analytic Hierarchy Process multi-criteria decision making technique for application in the smart metropolitan city context, with the aim of analysing the sustainable development of energy, water and environmental systems, through a set of objective performance indicators. Specifically, the 35 indicators defined for the Sustainable Development of Energy, Water and Environment Systems Index framework are used. The application of the approach to the real case study of four metropolitan areas (Bari, Bitonto, Mola, and Molfetta) in the city of Bari (Italy) shows its usefulness for the local government in benchmarking metropolitan areas and providing decision indications on how to formulate the sustainable development strategy of the metropolitan city. Based on the Analytic Hierarchy Process characteristics, the results highlight that although one specific area (Mola in the considered case) is globally ranked at the first place, it is only ranked first with respect to some dimensions. Such a result has strong implications for the metropolitan city's manager who has the possibility to identify and implement targeted actions, which may be designed ad hoc to improve specific dimensions based on the current state of the city, thus maximizing the efficiency and effectiveness of the actions undertaken for the sustainable development of energy, water and environmental systems of the whole metropolitan city. © 2018 Elsevier Ltd},
  author_keywords = {Analytic hierarchy process; Multi-criteria decision making; Performance evaluation; Planning; Sustainable development},
  keywords = {Cities; Conservation of Natural Resources; Decision Making; Europe; Italy; Bari [Bari (ADS)]; Bari [Puglia]; Italy; Puglia; Analytic hierarchy process; Benchmarking; Decision making; Energy systems; Environmental systems; Integrated management; Metropolitan area; Metropolitan cities; Multi criteria decision-making; Multicriteria decision-making; Multicriterion decision makings; Performances evaluation; Water system; analytical hierarchy process; assessment method; benchmarking; decision making; development strategy; local government; metropolitan area; multicriteria analysis; optimization; performance assessment; sustainability; sustainable development; urban planning; Article; benchmarking; city; decision making; energy resource; environmental sustainability; government; Italy; sustainable development; water supply; city; environmental protection; Europe; Sustainable development},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 93}
  }

2017

• Carli, R., Dotoli, M., Garramone, R., Andria, G. & Lanzolla, A. M. L. (2017) An average consensus approach for the optimal allocation of a shared renewable energy source IN 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 – Conference Proceedings., 270 – 275. doi:10.1109/SMC.2016.7844253
  [BibTeX] [Abstract] [Download PDF]

  This paper investigates the problem of optimally distributing the energy produced by a shared renewable energy source among users, without relying on a centralized decision maker. We assume that each user is only allowed to communicate with his neighbors and buys energy from a producer under non-linear pricing. We formulate a quadratic programming problem aimed at ensuring a social welfare-optimal allocation of the shared resource. We propose a low-complexity distributed algorithm that relies on average consensus. We show the convergence of the proposed algorithm to the unique optimal solution of the resource allocation problem. We also provide numerical simulations demonstrating that the approach allows exploiting the potential of renewable energy sources’ sharing to reduce users’ energy consumption costs. © 2016 IEEE.

  @CONFERENCE{Carli2017270,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Garramone, Raffaele and Andria, Gregorio and Lanzolla, Anna Maria Lucia},
  title = {An average consensus approach for the optimal allocation of a shared renewable energy source},
  year = {2017},
  journal = {2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings},
  pages = {270 – 275},
  doi = {10.1109/SMC.2016.7844253},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015803915&doi=10.1109%2fSMC.2016.7844253&partnerID=40&md5=8769614afb1c81c7bc718b4190b95117},
  abstract = {This paper investigates the problem of optimally distributing the energy produced by a shared renewable energy source among users, without relying on a centralized decision maker. We assume that each user is only allowed to communicate with his neighbors and buys energy from a producer under non-linear pricing. We formulate a quadratic programming problem aimed at ensuring a social welfare-optimal allocation of the shared resource. We propose a low-complexity distributed algorithm that relies on average consensus. We show the convergence of the proposed algorithm to the unique optimal solution of the resource allocation problem. We also provide numerical simulations demonstrating that the approach allows exploiting the potential of renewable energy sources' sharing to reduce users' energy consumption costs. © 2016 IEEE.},
  author_keywords = {Average consensus; Distributed optimization; Energy management; Multi-period resource allocation; Renewable energy sources},
  keywords = {Computational complexity; Cybernetics; Decision making; Economics; Energy management; Energy utilization; Natural resources; Optimization; Quadratic programming; Resource allocation; Average consensus; Distributed optimization; Multi-period; Non-linear pricing; Optimal allocation; Quadratic programming problems; Renewable energy source; Resource allocation problem; Renewable energy resources},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Ben Othman, S., Zgaya, H., Dotoli, M. & Hammadi, S. (2017) An agent-based Decision Support System for resources’ scheduling in Emergency Supply Chains. IN Control Engineering Practice, 59.27 – 43. doi:10.1016/j.conengprac.2016.11.014
  [BibTeX] [Abstract] [Download PDF]

  We propose a multi-agent-based architecture for the management of Emergency Supply Chains (ESCs), in which each zone is controlled by an agent. A Decision Support System (DSS) states and solves, in a distributed way, the scheduling problem for the delivery of resources from the ESC supplying zones to the ESC crisis-affected areas. Thanks to the agents’ cooperation, the DSS provides a scheduling plan that guarantees an effective response to emergencies. The approach is applied to two real cases: the Mali and the Japan crisis. Simulations are based on real data that have been validated by a team of logisticians from Airbus Defense and Space. © 2016 Elsevier Ltd

  @ARTICLE{Ben Othman201727,
  author = {Ben Othman, Sarah and Zgaya, Hayfa and Dotoli, Mariagrazia and Hammadi, Slim},
  title = {An agent-based Decision Support System for resources' scheduling in Emergency Supply Chains},
  year = {2017},
  journal = {Control Engineering Practice},
  volume = {59},
  pages = {27 – 43},
  doi = {10.1016/j.conengprac.2016.11.014},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84999780416&doi=10.1016%2fj.conengprac.2016.11.014&partnerID=40&md5=80bf4e8f6db808a74e12a1d923d84124},
  abstract = {We propose a multi-agent-based architecture for the management of Emergency Supply Chains (ESCs), in which each zone is controlled by an agent. A Decision Support System (DSS) states and solves, in a distributed way, the scheduling problem for the delivery of resources from the ESC supplying zones to the ESC crisis-affected areas. Thanks to the agents’ cooperation, the DSS provides a scheduling plan that guarantees an effective response to emergencies. The approach is applied to two real cases: the Mali and the Japan crisis. Simulations are based on real data that have been validated by a team of logisticians from Airbus Defense and Space. © 2016 Elsevier Ltd},
  author_keywords = {Crisis management; Decision Support System; Emergency Supply Chain; Multi-agent system; Scheduling},
  keywords = {Artificial intelligence; Multi agent systems; Scheduling; Supply chains; Affected area; Agent-based decision support systems; Crisis management; Decision support system (dss); Multi agent; Real case; Scheduling problem; Decision support systems},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 48; All Open Access, Green Open Access}
  }

• Dotoli, M. & Epicoco, N. (2017) A Vehicle Routing Technique for Hazardous Waste Collection IN IFAC-PapersOnLine., 9694 – 9699. doi:10.1016/j.ifacol.2017.08.2051
  [BibTeX] [Abstract] [Download PDF]

  Nowadays there is a growing interest in properly managing and collecting waste. Due to major threats on human health and environmental impact, hazardous waste management requires even much more attention. Nonetheless, in the literature there is a lack of techniques specifically devoted to the optimization of such a critical activity, which is characterized by more stringent constraints with respect to the typical municipal solid waste management. To fill this gap, we present a technique to solve the vehicle routing and scheduling problem for hazardous waste collection and disposal. The proposed method allows limiting the distance traveled by road (and therefore operating costs and emissions), enabling to match requests while respecting service time windows and vehicles’ availability. The technique also allows performing what-if analyses to evaluate the benefits arising from future investments in the fleet. The effectiveness of the method is shown by a real case study. © 2017

  @CONFERENCE{Dotoli20179694,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola},
  title = {A Vehicle Routing Technique for Hazardous Waste Collection},
  year = {2017},
  journal = {IFAC-PapersOnLine},
  volume = {50},
  number = {1},
  pages = {9694 – 9699},
  doi = {10.1016/j.ifacol.2017.08.2051},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031805728&doi=10.1016%2fj.ifacol.2017.08.2051&partnerID=40&md5=da5f048c9dfb57aff3692a450f9360b2},
  abstract = {Nowadays there is a growing interest in properly managing and collecting waste. Due to major threats on human health and environmental impact, hazardous waste management requires even much more attention. Nonetheless, in the literature there is a lack of techniques specifically devoted to the optimization of such a critical activity, which is characterized by more stringent constraints with respect to the typical municipal solid waste management. To fill this gap, we present a technique to solve the vehicle routing and scheduling problem for hazardous waste collection and disposal. The proposed method allows limiting the distance traveled by road (and therefore operating costs and emissions), enabling to match requests while respecting service time windows and vehicles’ availability. The technique also allows performing what-if analyses to evaluate the benefits arising from future investments in the fleet. The effectiveness of the method is shown by a real case study. © 2017},
  author_keywords = {Hazardous Waste; Optimization; Scheduling; Vehicle Routing},
  keywords = {Hazardous materials; Hazards; Health risks; Operating costs; Optimization; Scheduling; Vehicle routing; Vehicles; Waste disposal; Critical activities; Hazardous waste management; Hazardous wastes; Routing techniques; Service time; Stringent constraints; Vehicle routing and scheduling; What-if Analysis; Municipal solid waste},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 29; All Open Access, Gold Open Access}
  }

• Carli, R. & Dotoli, M. (2017) Cooperative Distributed Control for the Energy Scheduling of Smart Homes with Shared Energy Storage and Renewable Energy Source IN IFAC-PapersOnLine., 8867 – 8872. doi:10.1016/j.ifacol.2017.08.1544
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a distributed control technique for the energy scheduling of a group of interconnected smart city residential users. The proposed model aims at a simultaneous cost-optimal planning of users’ controllable appliances and of the shared storage system charge/discharge and renewable energy source. The distributed control algorithm is based on an iterative procedure combining parametric optimization with the block coordinate descent method. A realistic case study simulated in different scenarios demonstrates that the approach allows fully exploiting the potential of storage systems sharing to reduce individual users’ energy consumption costs and limit the peak average ratio of the energy profiles. © 2017

  @CONFERENCE{Carli20178867,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Cooperative Distributed Control for the Energy Scheduling of Smart Homes with Shared Energy Storage and Renewable Energy Source},
  year = {2017},
  journal = {IFAC-PapersOnLine},
  volume = {50},
  number = {1},
  pages = {8867 – 8872},
  doi = {10.1016/j.ifacol.2017.08.1544},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031787804&doi=10.1016%2fj.ifacol.2017.08.1544&partnerID=40&md5=9d6a82e7d9f16756a8d263254e537f45},
  abstract = {This paper presents a distributed control technique for the energy scheduling of a group of interconnected smart city residential users. The proposed model aims at a simultaneous cost-optimal planning of users’ controllable appliances and of the shared storage system charge/discharge and renewable energy source. The distributed control algorithm is based on an iterative procedure combining parametric optimization with the block coordinate descent method. A realistic case study simulated in different scenarios demonstrates that the approach allows fully exploiting the potential of storage systems sharing to reduce individual users’ energy consumption costs and limit the peak average ratio of the energy profiles. © 2017},
  author_keywords = {Decentralized; Distributed Control; Distribution Management Systems; Energy; Energy Storage Operation; Large scale optimization problems; Planning; Smart Grids},
  keywords = {Automation; Distributed parameter control systems; Energy storage; Energy utilization; Intelligent buildings; Iterative methods; Natural resources; Planning; Renewable energy resources; Scheduling; Decentralized; Distributed control; Distribution management systems; Energy; Large-scale optimization; Smart grid; Storage operations; Smart power grids},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 37; All Open Access, Gold Open Access}
  }

• Dotoli, M., Zgaya, H., Russo, C. & Hammadi, S. (2017) A Multi-Agent Advanced Traveler Information System for Optimal Trip Planning in a Co-Modal Framework. IN IEEE Transactions on Intelligent Transportation Systems, 18.2397 – 2412. doi:10.1109/TITS.2016.2645278
  [BibTeX] [Abstract] [Download PDF]

  We present an advanced traveler information system (ATIS) for public and private transportation, including vehicle sharing and pooling services. The ATIS uses an agent-based architecture and multi-objective optimization to answer trip planning requests from multiple users in a co-modal setting, considering vehicle preferences and conflicting criteria. At each set of users’ requests, the transportation network is represented by a co-modal graph that allows decomposing the trip planning problem into smaller tasks: the shortest routes between the network nodes are determined and then combined to obtain possible itineraries. Using multi-objective optimization, the set of user-vehicle-route combinations according to the users’ preferences is determined, ranking all possible route agents’ coalitions. The ATIS is tested for the real case study of the Lille metropolitan area (Nord Pas de Calais, France). © 2000-2011 IEEE.

  @ARTICLE{Dotoli20172397,
  author = {Dotoli, Mariagrazia and Zgaya, Hayfa and Russo, Carmine and Hammadi, Slim},
  title = {A Multi-Agent Advanced Traveler Information System for Optimal Trip Planning in a Co-Modal Framework},
  year = {2017},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
  volume = {18},
  number = {9},
  pages = {2397 – 2412},
  doi = {10.1109/TITS.2016.2645278},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010672602&doi=10.1109%2fTITS.2016.2645278&partnerID=40&md5=b70a67bc023c289ae5cecf8b537ae41f},
  abstract = {We present an advanced traveler information system (ATIS) for public and private transportation, including vehicle sharing and pooling services. The ATIS uses an agent-based architecture and multi-objective optimization to answer trip planning requests from multiple users in a co-modal setting, considering vehicle preferences and conflicting criteria. At each set of users' requests, the transportation network is represented by a co-modal graph that allows decomposing the trip planning problem into smaller tasks: the shortest routes between the network nodes are determined and then combined to obtain possible itineraries. Using multi-objective optimization, the set of user-vehicle-route combinations according to the users' preferences is determined, ranking all possible route agents' coalitions. The ATIS is tested for the real case study of the Lille metropolitan area (Nord Pas de Calais, France). © 2000-2011 IEEE.},
  author_keywords = {Advanced traveler information system; co-modal transport; directed graphs; multi-agent systems; optimization; private transport; public transport; trip planning},
  keywords = {Advanced public transportation systems; Information systems; Multi agent systems; Multiobjective optimization; Transportation routes; Vehicles; Agent based architectures; Metropolitan area; Multiple user; Network node; Private transportation; Shortest route; Transportation network; Trip planning; Advanced traveler information systems},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 30; All Open Access, Green Open Access}
  }

• Carli, R. & Dotoli, M. (2017) A decentralized control strategy for energy retrofit planning of large-scale street lighting systems using dynamic programming IN IEEE International Conference on Automation Science and Engineering., 1196 – 1200. doi:10.1109/COASE.2017.8256266
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses the energy management of large-scale urban street lighting systems. We propose a multi-stage decision-making procedure that supports the energy manager in determining the optimal energy retrofit plan of an existing public street lighting system. The problem statement is based on a quadratic integer programming formulation and aims at simultaneously reducing the energy consumption, ensuring an optimal allocation of the retrofit actions, and efficiently using the available budget. The proposed solution relies on a decentralized optimization algorithm that is based on discrete dynamic programming. The methodology is applied to a real street lighting system in the city of Bari, Italy. © 2017 IEEE.

  @CONFERENCE{Carli20171196,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A decentralized control strategy for energy retrofit planning of large-scale street lighting systems using dynamic programming},
  year = {2017},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2017-August},
  pages = {1196 – 1200},
  doi = {10.1109/COASE.2017.8256266},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044970276&doi=10.1109%2fCOASE.2017.8256266&partnerID=40&md5=7f8ba32dffa1946d990b4fa9bdfa7a59},
  abstract = {This paper addresses the energy management of large-scale urban street lighting systems. We propose a multi-stage decision-making procedure that supports the energy manager in determining the optimal energy retrofit plan of an existing public street lighting system. The problem statement is based on a quadratic integer programming formulation and aims at simultaneously reducing the energy consumption, ensuring an optimal allocation of the retrofit actions, and efficiently using the available budget. The proposed solution relies on a decentralized optimization algorithm that is based on discrete dynamic programming. The methodology is applied to a real street lighting system in the city of Bari, Italy. © 2017 IEEE.},
  keywords = {Budget control; Decision making; Energy management; Energy management systems; Energy utilization; Integer programming; Lighting fixtures; Retrofitting; Street lighting; Decentralized optimization; Decision making procedure; Energy managers; Optimal allocation; Problem statement; Quadratic integer programming; Retrofit actions; Street lighting system; Dynamic programming},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Carli, R., Dotoli, M. & Pellegrino, R. (2017) A Hierarchical Decision-Making Strategy for the Energy Management of Smart Cities. IN IEEE Transactions on Automation Science and Engineering, 14.505 – 523. doi:10.1109/TASE.2016.2593101
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a hierarchical decision-making strategy for the energy management of a smart city. The proposed decision process supports the city energy manager and local policy makers in taking energy retrofit decisions on different urban sectors by an integrated, structured, and transparent management. To this aim, in the proposed decision strategy, a bilevel programming model integrates several local decision-making units, each focusing on the energy retrofit optimization of a specific urban subsystem, and a central decision unit. We solve the hierarchical decision problem by a game theoretic distributed algorithm. We apply the developed decision model to the case study of the city of Bari (Italy), where a smart city program has recently been launched. © 2015 IEEE.

  @ARTICLE{Carli2017505,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Pellegrino, Roberta},
  title = {A Hierarchical Decision-Making Strategy for the Energy Management of Smart Cities},
  year = {2017},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {14},
  number = {2},
  pages = {505 – 523},
  doi = {10.1109/TASE.2016.2593101},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027724511&doi=10.1109%2fTASE.2016.2593101&partnerID=40&md5=b6d44e7085576476833b789dae66c70a},
  abstract = {This paper presents a hierarchical decision-making strategy for the energy management of a smart city. The proposed decision process supports the city energy manager and local policy makers in taking energy retrofit decisions on different urban sectors by an integrated, structured, and transparent management. To this aim, in the proposed decision strategy, a bilevel programming model integrates several local decision-making units, each focusing on the energy retrofit optimization of a specific urban subsystem, and a central decision unit. We solve the hierarchical decision problem by a game theoretic distributed algorithm. We apply the developed decision model to the case study of the city of Bari (Italy), where a smart city program has recently been launched. © 2015 IEEE.},
  author_keywords = {Bilevel programming; energy efficiency; energy management; game theory; hierarchical decision making; optimization; smart city},
  keywords = {Decision theory; Energy efficiency; Energy management; Game theory; Optimization; Retrofitting; Smart city; Bi-level programming; Bilevel programming models; Decision modeling; Decision process; Decision strategy; Energy retrofit; Hierarchical decisions; Local decision-making; Decision making},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 69}
  }

• Cavone, G., Dotoli, M., Epicoco, N. & Seatzu, C. (2017) Intermodal terminal planning by Petri Nets and Data Envelopment Analysis. IN Control Engineering Practice, 69.9 – 22. doi:10.1016/j.conengprac.2017.08.007
  [BibTeX] [Abstract] [Download PDF]

  A procedure for planning and resources’ management in intermodal terminals is presented. It integrates Timed Petri Nets (TPNs) and Data Envelopment Analysis (DEA) and consists of three steps: the terminal modeling via TPNs to model the regular behavior; the evaluation of whether the current configuration may cope with increased freight flows; if not, the analysis by cross-efficiency DEA of alternative planning solutions. The procedure provides the decision maker with number, capacity, and schedule of resources to tackle the flows increase. The method is evaluated by a real case study, showing that integrating TPNs and DEA allows taking planning decisions under conflicting requirements. © 2017

  @ARTICLE{Cavone20179,
  author = {Cavone, Graziana and Dotoli, Mariagrazia and Epicoco, Nicola and Seatzu, Carla},
  title = {Intermodal terminal planning by Petri Nets and Data Envelopment Analysis},
  year = {2017},
  journal = {Control Engineering Practice},
  volume = {69},
  pages = {9 – 22},
  doi = {10.1016/j.conengprac.2017.08.007},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028873437&doi=10.1016%2fj.conengprac.2017.08.007&partnerID=40&md5=f1dac97345f97f58a4fee381c92037d4},
  abstract = {A procedure for planning and resources’ management in intermodal terminals is presented. It integrates Timed Petri Nets (TPNs) and Data Envelopment Analysis (DEA) and consists of three steps: the terminal modeling via TPNs to model the regular behavior; the evaluation of whether the current configuration may cope with increased freight flows; if not, the analysis by cross-efficiency DEA of alternative planning solutions. The procedure provides the decision maker with number, capacity, and schedule of resources to tackle the flows increase. The method is evaluated by a real case study, showing that integrating TPNs and DEA allows taking planning decisions under conflicting requirements. © 2017},
  author_keywords = {Data Envelopment Analysis; Freight transportation; Intermodal terminals; Performance evaluation; Petri Nets; Resource planning},
  keywords = {Data envelopment analysis; Decision making; Freight transportation; Petri nets; Cross efficiency; Current configuration; Decision makers; Intermodal terminals; Performance evaluation; Resource planning; Terminal model; Timed Petri Net; Intermodal transportation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 29}
  }

• Dotoli, M. & Epicoco, N. (2017) A technique for the optimal management of containers’ drayage at intermodal terminals IN 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 – Conference Proceedings., 566 – 571. doi:10.1109/SMC.2016.7844300
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on optimizing one of the most critical activities in door-to-door intermodal transportation, i.e., the containers’ drayage by road. We present a technique to solve in an exact and optimal way the pick-up and delivery problem under the typical assumptions of intermodal transportation: full truck load, split delivery, clustered backhauls, and time windows. The method allows limiting the distance traveled by road, enabling to match a delivery with a pick-up request, while respecting customers’ service time windows, vehicles availability, and rental needs. Thus, intermodal companies can manage vehicle routing and scheduling problems in an integrated way. The technique effectiveness is shown by a real case study. © 2016 IEEE.

  @CONFERENCE{Dotoli2017566,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola},
  title = {A technique for the optimal management of containers' drayage at intermodal terminals},
  year = {2017},
  journal = {2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings},
  pages = {566 – 571},
  doi = {10.1109/SMC.2016.7844300},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015742748&doi=10.1109%2fSMC.2016.7844300&partnerID=40&md5=b4e0e9ba544f88a650a674ec969427ea},
  abstract = {This paper focuses on optimizing one of the most critical activities in door-to-door intermodal transportation, i.e., the containers' drayage by road. We present a technique to solve in an exact and optimal way the pick-up and delivery problem under the typical assumptions of intermodal transportation: full truck load, split delivery, clustered backhauls, and time windows. The method allows limiting the distance traveled by road, enabling to match a delivery with a pick-up request, while respecting customers' service time windows, vehicles availability, and rental needs. Thus, intermodal companies can manage vehicle routing and scheduling problems in an integrated way. The technique effectiveness is shown by a real case study. © 2016 IEEE.},
  keywords = {Containers; Cybernetics; Pickups; Roads and streets; Truck transportation; Vehicle routing; Critical activities; Full truck loads; Intermodal terminals; Optimal management; Pickup and delivery; Split delivery; Time windows; Vehicle routing and scheduling; Intermodal transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 4}
  }

• Carli, R. & Dotoli, M. (2017) A decentralized control strategy for optimal charging of electric vehicle fleets with congestion management IN Proceedings – 2017 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2017., 63 – 67. doi:10.1109/SOLI.2017.8120971
  [BibTeX] [Abstract] [Download PDF]

  This paper proposes a novel decentralized control strategy for the optimal charging of a large-scale fleet of Electric Vehicles (EVs). The scheduling problem aims at ensuring a cost-optimal profile of the aggregated energy demand and at satisfying the resource constraints depending both on power grid components capacity and EV locations in the distribution network. The resulting optimization problem is formulated as a quadratic programming problem with a coupling of decision variables both in the objective function and in the inequality constraints. The solution approach relies on a decentralized optimization algorithm that is based on a variant of ADMM (Alternating Direction Method of Multipliers), adapted to take into account the inequality constraints and the non-separated objective function. A simulated case study demonstrates that the approach allows achieving both the overall fleet and individual EV goals, while complying with the power grid congestion limits. © 2017 IEEE.

  @CONFERENCE{Carli201763,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A decentralized control strategy for optimal charging of electric vehicle fleets with congestion management},
  year = {2017},
  journal = {Proceedings - 2017 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2017},
  volume = {2017-January},
  pages = {63 – 67},
  doi = {10.1109/SOLI.2017.8120971},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046260212&doi=10.1109%2fSOLI.2017.8120971&partnerID=40&md5=2ced08ace41770b457c6f07d8cbe98b5},
  abstract = {This paper proposes a novel decentralized control strategy for the optimal charging of a large-scale fleet of Electric Vehicles (EVs). The scheduling problem aims at ensuring a cost-optimal profile of the aggregated energy demand and at satisfying the resource constraints depending both on power grid components capacity and EV locations in the distribution network. The resulting optimization problem is formulated as a quadratic programming problem with a coupling of decision variables both in the objective function and in the inequality constraints. The solution approach relies on a decentralized optimization algorithm that is based on a variant of ADMM (Alternating Direction Method of Multipliers), adapted to take into account the inequality constraints and the non-separated objective function. A simulated case study demonstrates that the approach allows achieving both the overall fleet and individual EV goals, while complying with the power grid congestion limits. © 2017 IEEE.},
  author_keywords = {Alternating direction method of multipliers; Congestion management; Coupled objective function; Decentralized optimization; Electric vehicle charging; Sharing},
  keywords = {Charging (batteries); Constraint satisfaction problems; Constraint theory; Decentralized control; Electric power transmission networks; Electric vehicles; Fleet operations; Quadratic programming; Traffic congestion; Alternating direction method of multipliers; Congestion management; Decentralized optimization; Electric vehicle charging; Objective functions; Sharing; Electric machine control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 12}
  }

• Dotoli, M., Epicoco, N., Falagario, M., Seatzu, C. & Turchiano, B. (2017) A decision support system for optimizing operations at intermodal railroad terminals. IN IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47.487 – 501. doi:10.1109/TSMC.2015.2506540
  [BibTeX] [Abstract] [Download PDF]

  In this paper, we present a decision support tool to optimize two of the most critical activities in intermodal railroad container terminals, in an iterative and integrated framework devoted to the terminal profit improvement. First, the model allows optimizing the freight trains composition, maximizing the company profit, while respecting physical and economic constraints, and placing in the train head/tail containers prosecuting to subsequent destinations. Hence, based on the resulting train composition, the decision support system allows optimizing the containers allocation in the terminal storage yard, in order to maximize the filling level while respecting physical constraints. The model is successfully tested on a real case study, the inland railroad terminal of a leading Italian intermodal logistics company. © 2013 IEEE.

  @ARTICLE{Dotoli2017487,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Seatzu, Carla and Turchiano, Biagio},
  title = {A decision support system for optimizing operations at intermodal railroad terminals},
  year = {2017},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems},
  volume = {47},
  number = {3},
  pages = {487 – 501},
  doi = {10.1109/TSMC.2015.2506540},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014711488&doi=10.1109%2fTSMC.2015.2506540&partnerID=40&md5=4dd2a6b2fba28746527bea33ec3dd762},
  abstract = {In this paper, we present a decision support tool to optimize two of the most critical activities in intermodal railroad container terminals, in an iterative and integrated framework devoted to the terminal profit improvement. First, the model allows optimizing the freight trains composition, maximizing the company profit, while respecting physical and economic constraints, and placing in the train head/tail containers prosecuting to subsequent destinations. Hence, based on the resulting train composition, the decision support system allows optimizing the containers allocation in the terminal storage yard, in order to maximize the filling level while respecting physical constraints. The model is successfully tested on a real case study, the inland railroad terminal of a leading Italian intermodal logistics company. © 2013 IEEE.},
  author_keywords = {Decision support system (DSS); intermodal freight transport; optimization; railroad terminal; train composition; yard container storage},
  keywords = {Containers; Filling; Freight transportation; Optimization; Profitability; Railroad stations; Railroad transportation; Railroad yards and terminals; Railroads; Truck terminals; Decision support system (dss); Decision support tools; Economic constraints; Integrated frameworks; Intermodal freight transport; Physical constraints; Rail-road terminals; Train composition; Decision support systems},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 33}
  }

• Guan, X., Zhao, Q., Jia, S. Q. & Dotoli, M. (2017) Welcome message from general and program chairs IN IEEE International Conference on Automation Science and Engineering., 1 – 3. doi:10.1109/COASE.2017.8256063
  [BibTeX] [Download PDF]

  @CONFERENCE{Guan20171,
  author = {Guan, Xiaohong and Zhao, Qianchuan and Jia, Samuel Qing-Shan and Dotoli, Mariagrazia},
  title = {Welcome message from general and program chairs},
  year = {2017},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2017-August},
  pages = {1 – 3},
  doi = {10.1109/COASE.2017.8256063},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044941166&doi=10.1109%2fCOASE.2017.8256063&partnerID=40&md5=7944ac6ea24984f7a7a4e1f04ef0bd32},
  type = {Editorial},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M., Epicoco, N. & Falagario, M. (2017) A fuzzy technique for supply chain network design with quantity discounts. IN International Journal of Production Research, 55.1862 – 1884. doi:10.1080/00207543.2016.1178408
  [BibTeX] [Abstract] [Download PDF]

  This paper proposes a hierarchical technique for Supply Chain Network (SCN) efficiency maximisation under uncertainty composed of three steps. The first step extends a previous fuzzy cross-efficiency Data Envelopment Analysis approach, originally intended for suppliers’ selection, in order to evaluate and rank all the actors in each SCN stage under conflicting nondeterministic criteria. Afterwards, a fuzzy linear integer programming model is stated and solved for each pair of subsequent SCN stages to determine the quantities required from each stakeholder to maximise the overall SCN efficiency while satisfying the estimated demand and respecting the nodes capacity. Finally, a heuristics is applied to limit the exchange of small quantities in the SCN, in which the trade is not economically convenient according to quantity discounts. An illustrative example from the literature shows the technique effectiveness. © 2016 Informa UK Limited, trading as Taylor & Francis Group.

  @ARTICLE{Dotoli20171862,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco},
  title = {A fuzzy technique for supply chain network design with quantity discounts},
  year = {2017},
  journal = {International Journal of Production Research},
  volume = {55},
  number = {7},
  pages = {1862 – 1884},
  doi = {10.1080/00207543.2016.1178408},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973872727&doi=10.1080%2f00207543.2016.1178408&partnerID=40&md5=cacc19478807834d6d9ab862bcee9b26},
  abstract = {This paper proposes a hierarchical technique for Supply Chain Network (SCN) efficiency maximisation under uncertainty composed of three steps. The first step extends a previous fuzzy cross-efficiency Data Envelopment Analysis approach, originally intended for suppliers’ selection, in order to evaluate and rank all the actors in each SCN stage under conflicting nondeterministic criteria. Afterwards, a fuzzy linear integer programming model is stated and solved for each pair of subsequent SCN stages to determine the quantities required from each stakeholder to maximise the overall SCN efficiency while satisfying the estimated demand and respecting the nodes capacity. Finally, a heuristics is applied to limit the exchange of small quantities in the SCN, in which the trade is not economically convenient according to quantity discounts. An illustrative example from the literature shows the technique effectiveness. © 2016 Informa UK Limited, trading as Taylor & Francis Group.},
  author_keywords = {cross-efficiency; data envelopment analysis; discount policy; fuzzy logic; optimisation; supply chain network design; uncertainty},
  keywords = {Data envelopment analysis; Efficiency; Integer programming; Supply chains; Uncertainty analysis; Cross efficiency; Discount policy; Optimisations; Supply chain network design; uncertainty; Fuzzy logic},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 28}
  }

• Carli, R. & Dotoli, M. (2017) Using the distributed proximal alternating direction method of multipliers for smart grid monitoring IN IEEE International Conference on Automation Science and Engineering., 418 – 423. doi:10.1109/COASE.2017.8256140
  [BibTeX] [Abstract] [Download PDF]

  Efficient and effective monitoring represents the starting point for a reliable and secure smart grid. Given the increasing size and complexity of power networks and the pressing concerns on privacy and robustness, the development of intelligent and flexible distributed monitoring systems represents a crucial issue in both structuring and operating future grids. In this context, this paper presents a distributed optimization framework for use in smart grid monitoring. We propose a distributed algorithm based on ADMM (Alternating Direction Method of Multipliers) for use in large scale optimization problems in smart grid monitoring. The proposed solution is based upon a local-based optimization process, where a limited amount of information is exchanged only between neighboring nodes in a locally broadcast fashion. Applying the approach to two illustrating examples demonstrates it allows exploiting the scalability and efficiency of distributed ADMM for distributed smart grid monitoring. © 2017 IEEE.

  @CONFERENCE{Carli2017418,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Using the distributed proximal alternating direction method of multipliers for smart grid monitoring},
  year = {2017},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2017-August},
  pages = {418 – 423},
  doi = {10.1109/COASE.2017.8256140},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044966539&doi=10.1109%2fCOASE.2017.8256140&partnerID=40&md5=dbecf71fd06d5b7c380c0ef1f2547de4},
  abstract = {Efficient and effective monitoring represents the starting point for a reliable and secure smart grid. Given the increasing size and complexity of power networks and the pressing concerns on privacy and robustness, the development of intelligent and flexible distributed monitoring systems represents a crucial issue in both structuring and operating future grids. In this context, this paper presents a distributed optimization framework for use in smart grid monitoring. We propose a distributed algorithm based on ADMM (Alternating Direction Method of Multipliers) for use in large scale optimization problems in smart grid monitoring. The proposed solution is based upon a local-based optimization process, where a limited amount of information is exchanged only between neighboring nodes in a locally broadcast fashion. Applying the approach to two illustrating examples demonstrates it allows exploiting the scalability and efficiency of distributed ADMM for distributed smart grid monitoring. © 2017 IEEE.},
  author_keywords = {ADMM; distributed optimization; monitoring; sensors network; smart grid},
  keywords = {Electric power transmission networks; Monitoring; ADMM; Alternating direction method of multipliers; Amount of information; Distributed monitoring systems; Distributed optimization; Large-scale optimization; Sensors network; Smart grid; Smart power grids},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Dotoli, M., Grammatico, S. & Ciulli, N. (2017) Guest Editorial Special Issue on Automation and Optimization for Energy Systems. IN IEEE Transactions on Automation Science and Engineering, 14.410 – 413. doi:10.1109/TASE.2017.2670758
  [BibTeX] [Download PDF]

  @ARTICLE{Dotoli2017410,
  author = {Dotoli, Mariagrazia and Grammatico, Sergio and Ciulli, Nicola},
  title = {Guest Editorial Special Issue on Automation and Optimization for Energy Systems},
  year = {2017},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {14},
  number = {2},
  pages = {410 – 413},
  doi = {10.1109/TASE.2017.2670758},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014814197&doi=10.1109%2fTASE.2017.2670758&partnerID=40&md5=553e7762a73691b7675d0cc34dfa8620},
  keywords = {Electrical engineering; Energy systems; Special sections; Automation},
  type = {Editorial},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M., Fay, A., Miśkowicz, M. & Seatzu, C. (2017) Advanced control in factory automation: a survey. IN International Journal of Production Research, 55.1243 – 1259. doi:10.1080/00207543.2016.1173259
  [BibTeX] [Abstract] [Download PDF]

  This paper provides a survey of the main advanced control techniques currently adopted in factory automation. In particular, it focuses on five classes of control approaches, namely: model-based control, control based on computational intelligence, adaptive control, discrete event systems-based control and finally event-triggered and self-triggered control. A particular focus is put on the most significant and recent contributions in these areas with attention to their application in the factory automation domain. Finally, open issues, challenges and the requirements of further research efforts for each class are pointed out. © 2016 Informa UK Limited, trading as Taylor & Francis Group.

  @ARTICLE{Dotoli20171243,
  author = {Dotoli, Mariagrazia and Fay, Alexander and Miśkowicz, Marek and Seatzu, Carla},
  title = {Advanced control in factory automation: a survey},
  year = {2017},
  journal = {International Journal of Production Research},
  volume = {55},
  number = {5},
  pages = {1243 – 1259},
  doi = {10.1080/00207543.2016.1173259},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963805196&doi=10.1080%2f00207543.2016.1173259&partnerID=40&md5=ea6c662282f1e090c503fff3e31d8e63},
  abstract = {This paper provides a survey of the main advanced control techniques currently adopted in factory automation. In particular, it focuses on five classes of control approaches, namely: model-based control, control based on computational intelligence, adaptive control, discrete event systems-based control and finally event-triggered and self-triggered control. A particular focus is put on the most significant and recent contributions in these areas with attention to their application in the factory automation domain. Finally, open issues, challenges and the requirements of further research efforts for each class are pointed out. © 2016 Informa UK Limited, trading as Taylor & Francis Group.},
  author_keywords = {adaptive control; advanced control; control based on computational intelligence; discrete event systems control; event-triggered control; factory automation; model predictive control; model-based control},
  keywords = {Artificial intelligence; Automation; Discrete event simulation; Factory automation; Model predictive control; Surveys; Adaptive Control; Advanced control; Control approach; Event-triggered; Event-triggered controls; Model based controls; Research efforts; Self-triggered controls; Adaptive control systems},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 31}
  }

• Cavone, G., Dotoli, M., Epicoco, N. & Seatzu, C. (2017) A decision making procedure for robust train rescheduling based on mixed integer linear programming and Data Envelopment Analysis. IN Applied Mathematical Modelling, 52.255 – 273. doi:10.1016/j.apm.2017.07.030
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a self-learning decision making procedure for robust real-time train rescheduling in case of disturbances. The procedure is applicable to aperiodic timetables of mixed-tracked networks and it consists of three steps. The first two are executed in real-time and provide the rescheduled timetable, while the third one is executed offline and guarantees the self-learning part of the method. In particular, in the first step, a robust timetable is determined, which is valid for a finite time horizon. This robust timetable is obtained solving a mixed integer linear programming problem aimed at finding the optimal compromise between two objectives: the minimization of the delays of the trains and the maximization of the robustness of the timetable. In the second step, a merging procedure is first used to join the obtained timetable with the nominal one. Then, a heuristics is applied to identify and solve all conflicts eventually arising after the merging procedure. Finally, in the third step an offline cross-efficiency fuzzy Data Envelopment Analysis technique is applied to evaluate the efficiency of the rescheduled timetable in terms of delays minimization and robustness maximization when different relevance weights (defining the compromise between the two optimization objectives) are used in the first step. The procedure is thus able to determine appropriate relevance weights to employ when disturbances of the same type affect again the network. The railway service provider can take advantage of this procedure to automate, optimize, and expedite the rescheduling process. Moreover, thanks to the self-learning capability of the procedure, the quality of the rescheduling is improved at each reapplication of the method. The technique is applied to a real data set related to a regional railway network in Southern Italy to test its effectiveness. © 2017 Elsevier Inc.

  @ARTICLE{Cavone2017255,
  author = {Cavone, Graziana and Dotoli, Mariagrazia and Epicoco, Nicola and Seatzu, Carla},
  title = {A decision making procedure for robust train rescheduling based on mixed integer linear programming and Data Envelopment Analysis},
  year = {2017},
  journal = {Applied Mathematical Modelling},
  volume = {52},
  pages = {255 – 273},
  doi = {10.1016/j.apm.2017.07.030},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032351265&doi=10.1016%2fj.apm.2017.07.030&partnerID=40&md5=9878b46aea5aa585ef08d87ee28e4b38},
  abstract = {This paper presents a self-learning decision making procedure for robust real-time train rescheduling in case of disturbances. The procedure is applicable to aperiodic timetables of mixed-tracked networks and it consists of three steps. The first two are executed in real-time and provide the rescheduled timetable, while the third one is executed offline and guarantees the self-learning part of the method. In particular, in the first step, a robust timetable is determined, which is valid for a finite time horizon. This robust timetable is obtained solving a mixed integer linear programming problem aimed at finding the optimal compromise between two objectives: the minimization of the delays of the trains and the maximization of the robustness of the timetable. In the second step, a merging procedure is first used to join the obtained timetable with the nominal one. Then, a heuristics is applied to identify and solve all conflicts eventually arising after the merging procedure. Finally, in the third step an offline cross-efficiency fuzzy Data Envelopment Analysis technique is applied to evaluate the efficiency of the rescheduled timetable in terms of delays minimization and robustness maximization when different relevance weights (defining the compromise between the two optimization objectives) are used in the first step. The procedure is thus able to determine appropriate relevance weights to employ when disturbances of the same type affect again the network. The railway service provider can take advantage of this procedure to automate, optimize, and expedite the rescheduling process. Moreover, thanks to the self-learning capability of the procedure, the quality of the rescheduling is improved at each reapplication of the method. The technique is applied to a real data set related to a regional railway network in Southern Italy to test its effectiveness. © 2017 Elsevier Inc.},
  author_keywords = {Data Envelopment Analysis; Decision making; Railways; Real-time; Rescheduling; Robustness},
  keywords = {Data envelopment analysis; Decision making; Efficiency; Merging; Optimization; Railroad transportation; Railroads; Robustness (control systems); Scheduling; Statistical tests; Transportation; Decision making procedure; Fuzzy data envelopment analysis; Mixed integer linear programming; Mixed integer linear programming problems; Railways; Real time; Rescheduling; Self-learning capability; Integer programming},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 40; All Open Access, Bronze Open Access}
  }

• Carli, R., Dotoli, M., Pellegrino, R. & Ranieri, L. (2017) A Decision Making Technique to Optimize a Buildings’ Stock Energy Efficiency. IN IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47.794 – 807. doi:10.1109/TSMC.2016.2521836
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on applying multicriteria decision making tools to determine an optimal energy retrofit plan for a portfolio of buildings. We present a two-step decision making technique employing a multiobjective optimization algorithm followed by a multiattribute ranking procedure. The method aims at deciding, in an integrated way, the optimal energy retrofit plan for a whole stock of buildings, optimizing efficiency, sustainability, and comfort, while effectively allocating the available financial resources to the buildings. The proposed methodology is applied to a real stock of public buildings in Bari, Italy. The obtained results demonstrate that the approach effectively supports the city governance in making decisions for the optimal management of the buildings’ energy efficiency. © 2016 IEEE.

  @ARTICLE{Carli2017794,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Pellegrino, Roberta and Ranieri, Luigi},
  title = {A Decision Making Technique to Optimize a Buildings' Stock Energy Efficiency},
  year = {2017},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems},
  volume = {47},
  number = {5},
  pages = {794 – 807},
  doi = {10.1109/TSMC.2016.2521836},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018489196&doi=10.1109%2fTSMC.2016.2521836&partnerID=40&md5=db70236a891233a4576656e616023e08},
  abstract = {This paper focuses on applying multicriteria decision making tools to determine an optimal energy retrofit plan for a portfolio of buildings. We present a two-step decision making technique employing a multiobjective optimization algorithm followed by a multiattribute ranking procedure. The method aims at deciding, in an integrated way, the optimal energy retrofit plan for a whole stock of buildings, optimizing efficiency, sustainability, and comfort, while effectively allocating the available financial resources to the buildings. The proposed methodology is applied to a real stock of public buildings in Bari, Italy. The obtained results demonstrate that the approach effectively supports the city governance in making decisions for the optimal management of the buildings' energy efficiency. © 2016 IEEE.},
  author_keywords = {Building management; energy efficiency; multiattribute analysis; multicriteria decision making; multiobjective optimization (MOO); optimization algorithms},
  keywords = {Buildings; Energy efficiency; Multiobjective optimization; Optimization; Retrofitting; Building management; Financial resources; Multi criteria decision making; Multi-attribute analysis; Multiattribute rankings; Optimal management; Optimization algorithms; Public buildings; Decision making},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 53}
  }

• Carli, R. & Dotoli, M. (2017) Bi-level programming for the energy retrofit planning of street lighting systems IN Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017., 543 – 548. doi:10.1109/ICNSC.2017.8000150
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses strategic decision making issues for the energy management of urban street lighting. We propose a hierarchical decision procedure that supports the energy manager in determining the optimal energy retrofit plan of an existing public street lighting system throughout a wide urban area. A bi-level programming model integrates several decision making units, each focusing on the energy optimization of a specific limited zone lighting system, and a central decision unit, aiming at a fair distribution of actions among these various systems, while ensuring an efficient use of public funds. We apply the technique to the case study of the city of Bari (Italy), to demonstrate the applicability and efficiency of the proposed optimization model. © 2017 IEEE.

  @CONFERENCE{Carli2017543,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Bi-level programming for the energy retrofit planning of street lighting systems},
  year = {2017},
  journal = {Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017},
  pages = {543 – 548},
  doi = {10.1109/ICNSC.2017.8000150},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028509849&doi=10.1109%2fICNSC.2017.8000150&partnerID=40&md5=7aa2cad3d9d4ab8f45ecac5cd40a808f},
  abstract = {This paper addresses strategic decision making issues for the energy management of urban street lighting. We propose a hierarchical decision procedure that supports the energy manager in determining the optimal energy retrofit plan of an existing public street lighting system throughout a wide urban area. A bi-level programming model integrates several decision making units, each focusing on the energy optimization of a specific limited zone lighting system, and a central decision unit, aiming at a fair distribution of actions among these various systems, while ensuring an efficient use of public funds. We apply the technique to the case study of the city of Bari (Italy), to demonstrate the applicability and efficiency of the proposed optimization model. © 2017 IEEE.},
  author_keywords = {Bilevel programming; Decision support system; Energy efficiency; Energy management; Hierarchical optimization; Street lighting},
  keywords = {Artificial intelligence; Decision making; Decision support systems; Energy efficiency; Energy management; Lighting; Lighting fixtures; Optimization; Retrofitting; Street lighting; Urban planning; Bi-level programming; Bilevel programming models; Decision making unit; Hierarchical decisions; Hierarchical optimization; Optimization modeling; Strategic decision making; Street lighting system; Energy management systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Carli, R., Dotoli, M. & Cianci, E. (2017) An optimization tool for energy efficiency of street lighting systems in smart cities IN IFAC-PapersOnLine., 14460 – 14464. doi:10.1016/j.ifacol.2017.08.2292
  [BibTeX] [Abstract] [Download PDF]

  This paper develops a decision making tool to support the public decision maker in selecting the optimal energy retrofit interventions on an existing street lighting system. The problem statement is based on a quadratic integer programming formulation and deals with simultaneously reducing the energy consumption and ensuring an optimal allocation of the retrofit actions among the street lighting subsystems. The methodology is applied to a real street lighting system in Bari, Italy. The obtained results demonstrate that the approach effectively supports the city governance in making decisions for the optimal energy management of the street lighting. © 2017

  @CONFERENCE{Carli201714460,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Cianci, Edmondo},
  title = {An optimization tool for energy efficiency of street lighting systems in smart cities},
  year = {2017},
  journal = {IFAC-PapersOnLine},
  volume = {50},
  number = {1},
  pages = {14460 – 14464},
  doi = {10.1016/j.ifacol.2017.08.2292},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042493832&doi=10.1016%2fj.ifacol.2017.08.2292&partnerID=40&md5=b1ee03a53ee4a57450cc0e590002a9e6},
  abstract = {This paper develops a decision making tool to support the public decision maker in selecting the optimal energy retrofit interventions on an existing street lighting system. The problem statement is based on a quadratic integer programming formulation and deals with simultaneously reducing the energy consumption and ensuring an optimal allocation of the retrofit actions among the street lighting subsystems. The methodology is applied to a real street lighting system in Bari, Italy. The obtained results demonstrate that the approach effectively supports the city governance in making decisions for the optimal energy management of the street lighting. © 2017},
  author_keywords = {Decision Making; Distribution Management Systems; Energy; Optimization; Smart Cities; Street Lighting},
  keywords = {Energy efficiency; Energy utilization; Integer programming; Lighting fixtures; Optimization; Retrofitting; Smart city; Street lighting; Decision making tool; Distribution management systems; Energy; Optimal allocation; Optimization tools; Problem statement; Quadratic integer programming; Street lighting system; Decision making},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 44; All Open Access, Gold Open Access}
  }

• Carli, R. & Dotoli, M. (2017) A distributed control algorithm for waterfilling of networked control systems via consensus. IN IEEE Control Systems Letters, 1.334 – 339. doi:10.1109/LCSYS.2017.2716190
  [BibTeX] [Abstract] [Download PDF]

  This letter presents a distributed waterfilling algorithm for networked control systems where users communicate with neighbors only. Waterfilling—a well-known optimization approach in communication systems—has inspired practical resolution methods for several control engineering and decision-making problems. This letter proposes a fully distributed solution for waterfilling of networked control systems. We consider multiple coupled waterlevels among users that locally communicate only with neighbors, without a central decision maker. We define two alternative versions (an exact one and an approximated one) of a novel distributed algorithm combining consensus, proximity, and the fixed point mapping theory, and show its convergence. We illustrate the technique by a case study on the charging of a fleet of electric vehicles. © 2017 IEEE.

  @ARTICLE{Carli2017334,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A distributed control algorithm for waterfilling of networked control systems via consensus},
  year = {2017},
  journal = {IEEE Control Systems Letters},
  volume = {1},
  number = {2},
  pages = {334 – 339},
  doi = {10.1109/LCSYS.2017.2716190},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050079250&doi=10.1109%2fLCSYS.2017.2716190&partnerID=40&md5=595d4be8879ccf3a42f0de75793d9038},
  abstract = {This letter presents a distributed waterfilling algorithm for networked control systems where users communicate with neighbors only. Waterfilling—a well-known optimization approach in communication systems—has inspired practical resolution methods for several control engineering and decision-making problems. This letter proposes a fully distributed solution for waterfilling of networked control systems. We consider multiple coupled waterlevels among users that locally communicate only with neighbors, without a central decision maker. We define two alternative versions (an exact one and an approximated one) of a novel distributed algorithm combining consensus, proximity, and the fixed point mapping theory, and show its convergence. We illustrate the technique by a case study on the charging of a fleet of electric vehicles. © 2017 IEEE.},
  author_keywords = {Distributed control; Networked control systems; Optimization},
  keywords = {Control theory; Decision making; Distributed parameter control systems; Fleet operations; Optimization; Decision makers; Decision-making problem; Distributed control; Distributed control algorithms; Distributed solutions; Optimization approach; Resolution methods; Water-filling algorithm; Networked control systems},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 30}
  }

2016

• Dotoli, M., Epicoco, N., Falagario, M. & Sciancalepore, F. (2016) A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty. IN International Transactions in Operational Research, 23.725 – 748. doi:10.1111/itor.12155
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses one of the key objectives of the supply chain strategic design phase, that is, the optimal selection of suppliers. A methodology for supplier selection under uncertainty is proposed, integrating the cross-efficiency data envelopment analysis (DEA) and Monte Carlo approach. The combination of these two techniques allows overcoming the deterministic feature of the classical cross-efficiency DEA approach. Moreover, we define an indicator of the robustness of the determined supplier ranking. The technique is able to manage the supplier selection problem considering nondeterministic input and output data. It allows the evaluation of suppliers under uncertainty, a particularly significant circumstance for the assessment of potential suppliers. The novel approach helps buyers in choosing the right partners under uncertainty and ranking suppliers upon a multiple sourcing strategy, even when considering complex evaluations with a high number of suppliers and many input and output criteria. © 2016 The Authors.

  @ARTICLE{Dotoli2016725,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Sciancalepore, Fabio},
  title = {A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty},
  year = {2016},
  journal = {International Transactions in Operational Research},
  volume = {23},
  number = {4},
  pages = {725 – 748},
  doi = {10.1111/itor.12155},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959365566&doi=10.1111%2fitor.12155&partnerID=40&md5=05c4875bc723279001f5267f45504640},
  abstract = {This paper addresses one of the key objectives of the supply chain strategic design phase, that is, the optimal selection of suppliers. A methodology for supplier selection under uncertainty is proposed, integrating the cross-efficiency data envelopment analysis (DEA) and Monte Carlo approach. The combination of these two techniques allows overcoming the deterministic feature of the classical cross-efficiency DEA approach. Moreover, we define an indicator of the robustness of the determined supplier ranking. The technique is able to manage the supplier selection problem considering nondeterministic input and output data. It allows the evaluation of suppliers under uncertainty, a particularly significant circumstance for the assessment of potential suppliers. The novel approach helps buyers in choosing the right partners under uncertainty and ranking suppliers upon a multiple sourcing strategy, even when considering complex evaluations with a high number of suppliers and many input and output criteria. © 2016 The Authors.},
  author_keywords = {Data envelopment analysis; Monte Carlo method; Supplier evaluation; Uncertainty modeling},
  keywords = {Data envelopment analysis; Efficiency; Monte Carlo methods; Stochastic systems; Uncertainty analysis; Complex evaluations; Input and outputs; Monte Carlo approach; Optimal selection; Sourcing strategies; Supplier Evaluations; Supplier selection; Uncertainty modeling; Supply chains},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 60}
  }

• Carli, R., Dotoli, M., Andria, G. & Lanzolla, A. M. L. (2016) Bi-level programming for the strategic energy management of a smart city IN EESMS 2016 – 2016 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems, Proceedings.. doi:10.1109/EESMS.2016.7504820
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses the emerging need for tools devoted to the strategic energy management of smart cities. We propose a novel decision model that supports the energy manager in governing the smart city while addressing different urban sectors with an integrated and structured energy retrofit planning. A bi-level programming model integrates several decision making units (decision panels), each focusing on the energy optimization of a specific urban subsystem, and a central decision unit. We solve the bi-level decision problem by a game theoretic distributed approach. We apply the developed decision model to the case study of the city of Bari (Italy), where a smart city program has recently been launched. © 2016 IEEE.

  @CONFERENCE{Carli2016,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Andria, Gregorio and Lanzolla, Anna Maria Lucia},
  title = {Bi-level programming for the strategic energy management of a smart city},
  year = {2016},
  journal = {EESMS 2016 - 2016 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems, Proceedings},
  doi = {10.1109/EESMS.2016.7504820},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84980371756&doi=10.1109%2fEESMS.2016.7504820&partnerID=40&md5=645711d93f3fee6a0e376fe0decdd093},
  abstract = {This paper addresses the emerging need for tools devoted to the strategic energy management of smart cities. We propose a novel decision model that supports the energy manager in governing the smart city while addressing different urban sectors with an integrated and structured energy retrofit planning. A bi-level programming model integrates several decision making units (decision panels), each focusing on the energy optimization of a specific urban subsystem, and a central decision unit. We solve the bi-level decision problem by a game theoretic distributed approach. We apply the developed decision model to the case study of the city of Bari (Italy), where a smart city program has recently been launched. © 2016 IEEE.},
  author_keywords = {bi-level programming; decision support system; distributed optimization; energy efficiency; energy management; smart city},
  keywords = {Artificial intelligence; Decision support systems; Distributed computer systems; Energy efficiency; Energy management; Game theory; Monitoring; Bi-level programming; Bilevel programming models; Decision making unit; Distributed approaches; Distributed optimization; Energy optimization; Smart cities; Strategic energy management; Decision making},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

• Cavone, G., Dotoli, M. & Seatzu, C. (2016) Management of Intermodal Freight Terminals by First-Order Hybrid Petri Nets. IN IEEE Robotics and Automation Letters, 1.2 – 9. doi:10.1109/LRA.2015.2502905
  [BibTeX] [Abstract] [Download PDF]

  In this paper, we show how first-order hybrid Petri nets can be efficiently used to model and manage intermodal freight transport terminals. The proposed formalism enables the terminal decision maker to choose the speeds associated with continuous transitions in order to optimize the terminal performance by two alternative control policies: the container flows maximization and the minimization of the residual containers in the storage area. The approach may be used either offline, to take decisions on the terminal resources, or online, to solve congestions/malfunctions. A real case study is modeled and managed by the proposed optimal control policies. © 2016 IEEE.

  @ARTICLE{Cavone20162,
  author = {Cavone, Graziana and Dotoli, Mariagrazia and Seatzu, Carla},
  title = {Management of Intermodal Freight Terminals by First-Order Hybrid Petri Nets},
  year = {2016},
  journal = {IEEE Robotics and Automation Letters},
  volume = {1},
  number = {1},
  pages = {2 – 9},
  doi = {10.1109/LRA.2015.2502905},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058585244&doi=10.1109%2fLRA.2015.2502905&partnerID=40&md5=5a498586aaee188bb2339dd6fff680ce},
  abstract = {In this paper, we show how first-order hybrid Petri nets can be efficiently used to model and manage intermodal freight transport terminals. The proposed formalism enables the terminal decision maker to choose the speeds associated with continuous transitions in order to optimize the terminal performance by two alternative control policies: the container flows maximization and the minimization of the residual containers in the storage area. The approach may be used either offline, to take decisions on the terminal resources, or online, to solve congestions/malfunctions. A real case study is modeled and managed by the proposed optimal control policies. © 2016 IEEE.},
  author_keywords = {Discrete Event Dynamic Automation Systems; Logistics; Petri Nets for Automation Control},
  keywords = {Automation; Bottling plants; Containers; Decision making; Logistics; Petri nets; Automation controls; Automation systems; Continuous transitions; Decision makers; First-order hybrid Petri nets; Intermodal freight; Intermodal freight transport; Optimal control policy; Freight transportation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 21}
  }

• Dotoli, M., Epicoco, N., Falagario, M. & Cavone, G. (2016) A Timed Petri Nets Model for Performance Evaluation of Intermodal Freight Transport Terminals. IN IEEE Transactions on Automation Science and Engineering, 13.842 – 857. doi:10.1109/TASE.2015.2404438
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a general modeling framework for Intermodal Freight Transport Terminals (IFTTs). The model allows simulating and evaluating the performance of such key elements of the intermodal transportation chain. Hence, it may be used by the decision maker to identify the IFTT bottlenecks, as well as to test different solutions to improve the IFTT dynamics. The proposed modeling framework is modular and based on timed Petri Nets (PNs), where places represent resources and capacities or conditions, transitions model inputs, flows, and activities into the terminal and tokens are intermodal transport units or the means on which they are transported. The model is able to represent the different types of existing IFTTs. Its effectiveness is tested first on an example from the literature and then on a real case study, the railroad inland terminal of a leading Italian intermodal logistics company, showing its ease of application. In the real case study, using the proposed formalism we test the as-is IFTT performance and evaluate alternative possible to-be improvements in order to identify and eliminate emerging criticalities in the terminal dynamics. © 2015 IEEE.

  @ARTICLE{Dotoli2016842,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Cavone, Graziana},
  title = {A Timed Petri Nets Model for Performance Evaluation of Intermodal Freight Transport Terminals},
  year = {2016},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {13},
  number = {2},
  pages = {842 – 857},
  doi = {10.1109/TASE.2015.2404438},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929017877&doi=10.1109%2fTASE.2015.2404438&partnerID=40&md5=04520d65c7c1306a86a7b871f538bcae},
  abstract = {This paper presents a general modeling framework for Intermodal Freight Transport Terminals (IFTTs). The model allows simulating and evaluating the performance of such key elements of the intermodal transportation chain. Hence, it may be used by the decision maker to identify the IFTT bottlenecks, as well as to test different solutions to improve the IFTT dynamics. The proposed modeling framework is modular and based on timed Petri Nets (PNs), where places represent resources and capacities or conditions, transitions model inputs, flows, and activities into the terminal and tokens are intermodal transport units or the means on which they are transported. The model is able to represent the different types of existing IFTTs. Its effectiveness is tested first on an example from the literature and then on a real case study, the railroad inland terminal of a leading Italian intermodal logistics company, showing its ease of application. In the real case study, using the proposed formalism we test the as-is IFTT performance and evaluate alternative possible to-be improvements in order to identify and eliminate emerging criticalities in the terminal dynamics. © 2015 IEEE.},
  author_keywords = {Discrete-event systems; intermodal freight transport; modeling; performance evaluation; simulation; timed Petri nets},
  keywords = {Decision making; Freight transportation; Petri nets; Decision makers; Inland Terminals; Intermodal freight transport; Intermodal transport; Logistics company; Model framework; Timed Petri Net; Timed Petri nets models; Intermodal transportation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 50}
  }

• Cavone, G., Dotoli, M. & Seatzu, C. (2016) Resource planning of intermodal terminals using timed Petri nets IN 2016 13th International Workshop on Discrete Event Systems, WODES 2016., 44 – 50. doi:10.1109/WODES.2016.7497824
  [BibTeX] [Abstract] [Download PDF]

  In this paper we show how timed Petri nets can be efficiently used to solve problems related to resource planning in intermodal freight transport terminals. In particular, the tackled issues regard the strategic planning of the number of facilities used to transfer the intermodal transport units and the capacity/frequency of the transportation means. A real case study is considered, namely a rail-road terminal located in southern Italy. Monte Carlo simulations based on the timed Petri net model of the terminal are carried out considering various scenarios, including both the regular behavior based on real data, and situations of potential congestion resulting from increase in the commercial flows. © 2016 IEEE.

  @CONFERENCE{Cavone201644,
  author = {Cavone, Graziana and Dotoli, Mariagrazia and Seatzu, Carla},
  title = {Resource planning of intermodal terminals using timed Petri nets},
  year = {2016},
  journal = {2016 13th International Workshop on Discrete Event Systems, WODES 2016},
  pages = {44 – 50},
  doi = {10.1109/WODES.2016.7497824},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84981302932&doi=10.1109%2fWODES.2016.7497824&partnerID=40&md5=6e380dff1ab12bf5ebd7b38ef41fe0ac},
  abstract = {In this paper we show how timed Petri nets can be efficiently used to solve problems related to resource planning in intermodal freight transport terminals. In particular, the tackled issues regard the strategic planning of the number of facilities used to transfer the intermodal transport units and the capacity/frequency of the transportation means. A real case study is considered, namely a rail-road terminal located in southern Italy. Monte Carlo simulations based on the timed Petri net model of the terminal are carried out considering various scenarios, including both the regular behavior based on real data, and situations of potential congestion resulting from increase in the commercial flows. © 2016 IEEE.},
  keywords = {Discrete event simulation; Freight transportation; Intelligent systems; Monte Carlo methods; Petri nets; Resource allocation; Scheduling algorithms; Traffic control; Behavior-based; Intermodal freight transport; Intermodal terminals; Intermodal transport; Rail-road terminals; Resource planning; Southern Italy; Timed Petri Net; Intermodal transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 16}
  }

• Dotoli, M., Epicoco, N. & Falagario, M. (2016) A technique for efficient multimodal transport planning with conflicting objectives under uncertainty IN 2016 European Control Conference, ECC 2016., 2441 – 2446. doi:10.1109/ECC.2016.7810656
  [BibTeX] [Abstract] [Download PDF]

  Multimodal freight transport is growing as a means to reduce environmental impact and road congestion, and to increase road safety. The proper planning and management of multimodal transport is a key issue to ensure the competitiveness of companies. In this paper we present a fuzzy cross-efficiency Data Envelopment Analysis (DEA) technique for efficient multimodal transport planning in a multi-objective perspective, under uncertainty, and with a high discriminative power. The approach is tested on a real case study, showing its effectiveness in determining the most efficient transport planning and in identifying the distance from which multimodality is more efficient than all-road transport. © 2016 EUCA.

  @CONFERENCE{Dotoli20162441,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco},
  title = {A technique for efficient multimodal transport planning with conflicting objectives under uncertainty},
  year = {2016},
  journal = {2016 European Control Conference, ECC 2016},
  pages = {2441 – 2446},
  doi = {10.1109/ECC.2016.7810656},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015015532&doi=10.1109%2fECC.2016.7810656&partnerID=40&md5=64b0c90acc204f7f0a66eee29673487d},
  abstract = {Multimodal freight transport is growing as a means to reduce environmental impact and road congestion, and to increase road safety. The proper planning and management of multimodal transport is a key issue to ensure the competitiveness of companies. In this paper we present a fuzzy cross-efficiency Data Envelopment Analysis (DEA) technique for efficient multimodal transport planning in a multi-objective perspective, under uncertainty, and with a high discriminative power. The approach is tested on a real case study, showing its effectiveness in determining the most efficient transport planning and in identifying the distance from which multimodality is more efficient than all-road transport. © 2016 EUCA.},
  keywords = {Data envelopment analysis; Freight transportation; Motor transportation; Roads and streets; Uncertainty analysis; Conflicting objectives; Cross-efficiency; Freight transport; Key Issues; Multi-modal; Multimodal transport; Road congestion; Road safety; Transport planning; Uncertainty; Environmental impact},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

2015

• Dotoli, M., Epicoco, N., Falagario, M., Costantino, N. & Turchiano, B. (2015) An integrated approach for warehouse analysis and optimization: A case study. IN Computers in Industry, 70.56 – 69. doi:10.1016/j.compind.2014.12.004
  [BibTeX] [Abstract] [Download PDF]

  The paper focuses on the analysis and optimization of production warehouses, proposing a novel approach to reduce inefficiencies which employs three lean manufacturing tools in an integrated and iterative framework. The proposed approach integrates the Unified Modeling Language (UML) – providing a detailed description of the warehouse logistics – the Value Stream Mapping (VSM) tool – identifying non-value adding activities – and a mathematical formulation of the so-called Genba Shikumi philosophy – ranking such system anomalies and assessing how they affect the warehouse. The subsequent reapplication of the VSM produces a complete picture of the reengineered warehouse, and using the UML tool allows describing in detail the updated system. By applying the presented methodology to the warehouse of an Italian interior design producer, we show that it represents a useful tool to systematically and dynamically improve the warehouse management. Indeed, the application of the approach to the company leads to an innovative proposal for the warehouse analysis and optimization: a warehouse management system that leads to increased profitability and quality as well as to reduced errors. © 2014 Elsevier B.V. All rights reserved.

  @ARTICLE{Dotoli201556,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Costantino, Nicola and Turchiano, Biagio},
  title = {An integrated approach for warehouse analysis and optimization: A case study},
  year = {2015},
  journal = {Computers in Industry},
  volume = {70},
  number = {1},
  pages = {56 – 69},
  doi = {10.1016/j.compind.2014.12.004},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84926355397&doi=10.1016%2fj.compind.2014.12.004&partnerID=40&md5=a12e368cf5ec2e7108d105646b343320},
  abstract = {The paper focuses on the analysis and optimization of production warehouses, proposing a novel approach to reduce inefficiencies which employs three lean manufacturing tools in an integrated and iterative framework. The proposed approach integrates the Unified Modeling Language (UML) - providing a detailed description of the warehouse logistics - the Value Stream Mapping (VSM) tool - identifying non-value adding activities - and a mathematical formulation of the so-called Genba Shikumi philosophy - ranking such system anomalies and assessing how they affect the warehouse. The subsequent reapplication of the VSM produces a complete picture of the reengineered warehouse, and using the UML tool allows describing in detail the updated system. By applying the presented methodology to the warehouse of an Italian interior design producer, we show that it represents a useful tool to systematically and dynamically improve the warehouse management. Indeed, the application of the approach to the company leads to an innovative proposal for the warehouse analysis and optimization: a warehouse management system that leads to increased profitability and quality as well as to reduced errors. © 2014 Elsevier B.V. All rights reserved.},
  author_keywords = {Analysis; Genba Shikumi; Optimization; Unified modeling language; Value stream mapping; Warehouse},
  keywords = {Architectural design; Computer hardware description languages; Industrial management; Iterative methods; Mapping; Optimization; Quality control; Unified Modeling Language; Analysis; Genba Shikumi; Manufacturing tools; Mathematical formulation; Value adding activities; Value stream mapping; Warehouse management; Warehouse management systems; Warehouses},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 64}
  }

• Dotoli, M., Epicoco, N. & Falagario, M. (2015) Integrated supplier selection and order allocation under uncertainty in agile supply chains IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA.. doi:10.1109/ETFA.2015.7301509
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on the supplier selection problem and the subsequent order allocation, extending an approach originally proposed by some of the authors for supplier ranking under uncertainty. The novel method integrates the cross-efficiency Data Envelopment Analysis and the fuzzy set theory to obtain a ranking of suppliers under nondeterministic evaluation criteria. Subsequently, a fuzzy integer linear programming model allows determining the quantities to require from each supplier as a compromise between the suppliers’ efficiency, procurement costs, and time required to fulfill the order, while respecting the suppliers’ capacity and satisfying the customers’ demand. The case study of an SME manufacturer shows the technique effectiveness. © 2015 IEEE.

  @CONFERENCE{Dotoli2015,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco},
  title = {Integrated supplier selection and order allocation under uncertainty in agile supply chains},
  year = {2015},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  volume = {2015-October},
  doi = {10.1109/ETFA.2015.7301509},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952912259&doi=10.1109%2fETFA.2015.7301509&partnerID=40&md5=0c2187c85b7474af8440d5fd9fd0f3f1},
  abstract = {This paper focuses on the supplier selection problem and the subsequent order allocation, extending an approach originally proposed by some of the authors for supplier ranking under uncertainty. The novel method integrates the cross-efficiency Data Envelopment Analysis and the fuzzy set theory to obtain a ranking of suppliers under nondeterministic evaluation criteria. Subsequently, a fuzzy integer linear programming model allows determining the quantities to require from each supplier as a compromise between the suppliers' efficiency, procurement costs, and time required to fulfill the order, while respecting the suppliers' capacity and satisfying the customers' demand. The case study of an SME manufacturer shows the technique effectiveness. © 2015 IEEE.},
  author_keywords = {agile supply chain; data envelopment analysis; fuzzy logic; manufacturing; order allocation; supplier selection; uncertainty},
  keywords = {Data envelopment analysis; Efficiency; Factory automation; Fuzzy logic; Fuzzy set theory; Integer programming; Manufacture; Supply chains; Agile supply chains; Cross efficiency; Evaluation criteria; Fuzzy integer linear programming; Order allocation; Procurement costs; Supplier selection; uncertainty; Uncertainty analysis},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 7}
  }

• Carli, R., Dotoli, M., Epicoco, N., Angelico, B. & Vinciullo, A. (2015) Automated evaluation of urban traffic congestion using bus as a probe IN IEEE International Conference on Automation Science and Engineering., 967 – 972. doi:10.1109/CoASE.2015.7294224
  [BibTeX] [Abstract] [Download PDF]

  This paper presents an algorithm for the automated analysis and evaluation of vehicular traffic congestion in urban areas. The proposed approach is based on the concept of bus as a probe and makes use of GPS-generated data provided by a local transit bus tracking system. Archived GPS pulses are analyzed offline to extract valuable indices related to general urban traffic characteristics and aimed at generating a detailed view of the urban roads congestion. This information is useful both for policy makers, to effectively address the management of sustainable mobility in urban areas, and for citizens, to acquire awareness about congestion times and location zones. The presented algorithm is applied to a part of the urban road network of the municipality of Bari (Italy). © 2015 IEEE.

  @CONFERENCE{Carli2015967,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Epicoco, Nicola and Angelico, Biagio and Vinciullo, Antonio},
  title = {Automated evaluation of urban traffic congestion using bus as a probe},
  year = {2015},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2015-October},
  pages = {967 – 972},
  doi = {10.1109/CoASE.2015.7294224},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952762623&doi=10.1109%2fCoASE.2015.7294224&partnerID=40&md5=c2588eba274a644410a09da25d3699b5},
  abstract = {This paper presents an algorithm for the automated analysis and evaluation of vehicular traffic congestion in urban areas. The proposed approach is based on the concept of bus as a probe and makes use of GPS-generated data provided by a local transit bus tracking system. Archived GPS pulses are analyzed offline to extract valuable indices related to general urban traffic characteristics and aimed at generating a detailed view of the urban roads congestion. This information is useful both for policy makers, to effectively address the management of sustainable mobility in urban areas, and for citizens, to acquire awareness about congestion times and location zones. The presented algorithm is applied to a part of the urban road network of the municipality of Bari (Italy). © 2015 IEEE.},
  keywords = {Algorithms; Automation; Buses; Motor transportation; Probes; Automated analysis; Automated evaluation; Policy makers; Sustainable mobility; Tracking system; Urban road networks; Urban traffic; Urban traffic congestion; Traffic congestion},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 32}
  }

• Dotoli, M., Epicoco, N., Falagario, M. & Sciancalepore, F. (2015) A cross-efficiency fuzzy Data Envelopment Analysis technique for performance evaluation of Decision Making Units under uncertainty. IN Computers and Industrial Engineering, 79.103 – 114. doi:10.1016/j.cie.2014.10.026
  [BibTeX] [Abstract] [Download PDF]

  The paper presents a novel cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique for evaluating different elements (Decision Making Units or DMUs) under uncertainty. In order to evaluate the performance of several DMUs while dealing with uncertain input and output data, the presented technique employs triangular fuzzy numbers. A fuzzy triangular efficiency is associated to each DMU through a cross evaluation obtained by a compromise between suitably chosen objectives. Results are then defuzzified to provide a ranking of the DMUs. The proposed method is applied to the performance evaluation of healthcare systems in a region of Southern Italy. The DMU data uncertainty derives from ongoing reforms and the reported assessment is conducted firstly in order to evaluate and rank the efficiency of the considered healthcare systems, and subsequently to assess the evolution of the performance of one of the most affected among these DMUs by the reform plans. The case study demonstrates the model ease of application, its discriminative power among DMUs when compared to a more classical fuzzy DEA approach, and the usefulness in planning and validating targeted reforms in the case of healthcare systems. © 2014 Elsevier Ltd.

  @ARTICLE{Dotoli2015103,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Sciancalepore, Fabio},
  title = {A cross-efficiency fuzzy Data Envelopment Analysis technique for performance evaluation of Decision Making Units under uncertainty},
  year = {2015},
  journal = {Computers and Industrial Engineering},
  volume = {79},
  pages = {103 – 114},
  doi = {10.1016/j.cie.2014.10.026},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911930890&doi=10.1016%2fj.cie.2014.10.026&partnerID=40&md5=921a7a2499b61f6594a4201bba8f8d73},
  abstract = {The paper presents a novel cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique for evaluating different elements (Decision Making Units or DMUs) under uncertainty. In order to evaluate the performance of several DMUs while dealing with uncertain input and output data, the presented technique employs triangular fuzzy numbers. A fuzzy triangular efficiency is associated to each DMU through a cross evaluation obtained by a compromise between suitably chosen objectives. Results are then defuzzified to provide a ranking of the DMUs. The proposed method is applied to the performance evaluation of healthcare systems in a region of Southern Italy. The DMU data uncertainty derives from ongoing reforms and the reported assessment is conducted firstly in order to evaluate and rank the efficiency of the considered healthcare systems, and subsequently to assess the evolution of the performance of one of the most affected among these DMUs by the reform plans. The case study demonstrates the model ease of application, its discriminative power among DMUs when compared to a more classical fuzzy DEA approach, and the usefulness in planning and validating targeted reforms in the case of healthcare systems. © 2014 Elsevier Ltd.},
  author_keywords = {Analysis; Cross-efficiency; Data; Decision making; Envelopment; Fuzzy logic; Performance evaluation; Uncertainty},
  keywords = {Data envelopment analysis; Efficiency; Fuzzy logic; Fuzzy sets; Health care; Uncertainty analysis; Analysis; Cross-efficiency; Data; Envelopment; Performance evaluation; Uncertainty; Decision making},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 124}
  }

• Dotoli, M., Epicoco, N., Falagario, M., Angelico, B. & Vinciullo, A. (2015) A two-step optimization model for the pre- and end-haulage of containers at intermodal freight terminals IN 2015 European Control Conference, ECC 2015., 3472 – 3477. doi:10.1109/ECC.2015.7331071
  [BibTeX] [Abstract] [Download PDF]

  The paper focuses on the optimization of containers pre- and end-haulage by road in intermodal terminals, which is one of the most critical factors in door to door transport effectiveness and profit. We present an optimization model that allows solving in an exact and optimal way the vehicle routing and fleet management problems. The model comprises two steps: first it optimizes the distance traveled by road, enabling to match a delivery with a pick up; the second step is devoted to minimizing the number of vehicles required for the deliveries, while satisfying the routes obtained from the previous step. The proposed optimization model is applied to a real case study to test its effectiveness. © 2015 EUCA.

  @CONFERENCE{Dotoli20153472,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Angelico, Biagio and Vinciullo, Antonio},
  title = {A two-step optimization model for the pre- and end-haulage of containers at intermodal freight terminals},
  year = {2015},
  journal = {2015 European Control Conference, ECC 2015},
  pages = {3472 – 3477},
  doi = {10.1109/ECC.2015.7331071},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963799902&doi=10.1109%2fECC.2015.7331071&partnerID=40&md5=025d5a96d0a749c51da62cd89b09b4fe},
  abstract = {The paper focuses on the optimization of containers pre- and end-haulage by road in intermodal terminals, which is one of the most critical factors in door to door transport effectiveness and profit. We present an optimization model that allows solving in an exact and optimal way the vehicle routing and fleet management problems. The model comprises two steps: first it optimizes the distance traveled by road, enabling to match a delivery with a pick up; the second step is devoted to minimizing the number of vehicles required for the deliveries, while satisfying the routes obtained from the previous step. The proposed optimization model is applied to a real case study to test its effectiveness. © 2015 EUCA.},
  keywords = {Containers; Fleet operations; Roads and streets; Critical factors; Fleet management; Intermodal freight; Intermodal terminals; Minimizing the number of; Optimization modeling; Real case; Two-step optimizations; Optimization},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

• Dotoli, M., Epicoco, N. & Seatzu, C. (2015) An improved technique for train load planning at intermodal rail-road terminals IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA.. doi:10.1109/ETFA.2015.7301580
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a train load planning technique for intermodal rail-road terminals. The proposed method aims at maximizing the train commercial value while respecting priority, physical, financial, and prosecution constraints (i.e., taking into account containers that prosecute their trip after the first destination). The approach consists of two phases: 1) modifying a previous approach by some of the authors, a linear integer programming problem is solved to maximize the train commercial value, keeping into account urgencies and priorities; 2) hence, a heuristics is used to take into account prosecuting containers and reduce the number of wagons to be re-handled. The technique is tested on a real case study and compared with the previous strategy proposed by some of the authors to show its effectiveness and ease of application. © 2015 IEEE.

  @CONFERENCE{Dotoli2015,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Seatzu, Carla},
  title = {An improved technique for train load planning at intermodal rail-road terminals},
  year = {2015},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  volume = {2015-October},
  doi = {10.1109/ETFA.2015.7301580},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952908064&doi=10.1109%2fETFA.2015.7301580&partnerID=40&md5=16668e6fa05111e7cfacf104b43ef027},
  abstract = {This paper presents a train load planning technique for intermodal rail-road terminals. The proposed method aims at maximizing the train commercial value while respecting priority, physical, financial, and prosecution constraints (i.e., taking into account containers that prosecute their trip after the first destination). The approach consists of two phases: 1) modifying a previous approach by some of the authors, a linear integer programming problem is solved to maximize the train commercial value, keeping into account urgencies and priorities; 2) hence, a heuristics is used to take into account prosecuting containers and reduce the number of wagons to be re-handled. The technique is tested on a real case study and compared with the previous strategy proposed by some of the authors to show its effectiveness and ease of application. © 2015 IEEE.},
  author_keywords = {intermodal freight transport; load planning; optimization; rail-road transport; train composition},
  keywords = {Containers; Factory automation; Freight transportation; Optimization; Railroads; Roads and streets; Transportation; Improved techniques; Intermodal freight transport; Linear integer programming; Load planning; Rail-road terminals; Real case; Train composition; Train loads; Integer programming},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 9}
  }

• Dotoli, M., Fay, A., Miskowicz, M. & Seatzu, C. (2015) A survey on advanced control approaches in factory automation IN IFAC-PapersOnLine., 394 – 399. doi:10.1016/j.ifacol.2015.06.113
  [BibTeX] [Abstract] [Download PDF]

  The goal of this paper consists in providing a survey of the main advanced control techniques currently adopted in factory automation. In particular, attention is devoted to model based control, model predictive control, intelligent and adaptive control, discrete event and event-triggered control. Open issues and challenges are pointed out, and the needs for further research efforts are discussed in detail. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

  @CONFERENCE{Dotoli2015394,
  author = {Dotoli, Mariagrazia and Fay, Alexander and Miskowicz, Marek and Seatzu, Carla},
  title = {A survey on advanced control approaches in factory automation},
  year = {2015},
  journal = {IFAC-PapersOnLine},
  volume = {28},
  number = {3},
  pages = {394 – 399},
  doi = {10.1016/j.ifacol.2015.06.113},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953865196&doi=10.1016%2fj.ifacol.2015.06.113&partnerID=40&md5=7487e152c395d18b98f21b4ebcbe27f2},
  abstract = {The goal of this paper consists in providing a survey of the main advanced control techniques currently adopted in factory automation. In particular, attention is devoted to model based control, model predictive control, intelligent and adaptive control, discrete event and event-triggered control. Open issues and challenges are pointed out, and the needs for further research efforts are discussed in detail. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},
  author_keywords = {Adaptive control; Advanced control; Discrete event control; Event-triggered control; Factory automation; Intelligent control; Model based control; Model predictive control},
  keywords = {Discrete event simulation; Factory automation; Intelligent control; Surveys; Adaptive control systems; Adaptive Control; Advanced control; Discrete event control; Event-triggered controls; Model based controls; Control approach; Control model; Control techniques; Discrete events; Model-predictive control; Model predictive control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 8; All Open Access, Gold Open Access}
  }

• Carli, R., Albino, V., Dotoli, M., Mummolo, G. & Savino, M. (2015) A dashboard and decision support tool for the energy governance of smart cities IN 2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems, EESMS 2015 – Proceedings., 23 – 28. doi:10.1109/EESMS.2015.7175846
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the findings of the research activities conducted in the framework of the RES NOVAE project for the design and development of the Urban Control Center (UCC), a control room of the smart city that allows the Public Administration to analyze the city dynamics and citizens to receive information on the performance of urban infrastructure and services. With a specific focus on energy efficiency and environmental sustainability, we present the architecture of an innovative dashboard and decision support tool for efficient urban governance. We investigate solutions to effectively measure the city energy performance and proficiently support the decision maker in determining the optimal action plan for implementing smartness strategies in the city energy governance. © 2015 IEEE.

  @CONFERENCE{Carli201523,
  author = {Carli, Raffaele and Albino, Vito and Dotoli, Mariagrazia and Mummolo, Giovanni and Savino, Mario},
  title = {A dashboard and decision support tool for the energy governance of smart cities},
  year = {2015},
  journal = {2015 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems, EESMS 2015 - Proceedings},
  pages = {23 – 28},
  doi = {10.1109/EESMS.2015.7175846},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84950984321&doi=10.1109%2fEESMS.2015.7175846&partnerID=40&md5=675d5e25da8794e638be9ff52797dd47},
  abstract = {The paper addresses the findings of the research activities conducted in the framework of the RES NOVAE project for the design and development of the Urban Control Center (UCC), a control room of the smart city that allows the Public Administration to analyze the city dynamics and citizens to receive information on the performance of urban infrastructure and services. With a specific focus on energy efficiency and environmental sustainability, we present the architecture of an innovative dashboard and decision support tool for efficient urban governance. We investigate solutions to effectively measure the city energy performance and proficiently support the decision maker in determining the optimal action plan for implementing smartness strategies in the city energy governance. © 2015 IEEE.},
  author_keywords = {decision support system; energy efficiency; indicators dashboard; information and communication technologies; management; monitoring; multi-attribute analysis; multi-objective optimization; optimization; smart cities},
  keywords = {Artificial intelligence; Decision making; Decision support systems; Information management; Management; Monitoring; Multiobjective optimization; Optimization; Public administration; Sustainable development; Decision support tools; Design and Development; Environmental sustainability; Information and Communication Technologies; Multi-attribute analysis; Research activities; Smart cities; Urban infrastructure; Energy efficiency},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Carli, R. & Dotoli, M. (2015) A decentralized resource allocation approach for sharing renewable energy among interconnected smart homes IN Proceedings of the IEEE Conference on Decision and Control., 5903 – 5908. doi:10.1109/CDC.2015.7403147
  [BibTeX] [Abstract] [Download PDF]

  The paper deals with the scheduling of energy activities of a group of interconnected users that buy energy from a producer and share a renewable energy source. The scheduling problem is stated and solved with a twofold goal. First, the model is formulated to ensure social welfare-optimal allocation of the energy produced from the shared renewable energy generator. Second, the model aims at cost-optimal planning of users’ controllable appliances taking into account a realistic time-varying quadratic pricing of the energy bought from the distribution network. The solution approach relies on a decentralized optimization algorithm that is composed by a two-level iterative procedure combining Gauss-Seidel decomposition with competitive game formulation. A case study simulated in different scenarios demonstrates that the approach allows exploiting the potential of renewable energy sources’ sharing to reduce individual users’ energy consumption costs, limiting the peak average ratio of energy profiles and complying with the customer’s energy needs. © 2015 IEEE.

  @CONFERENCE{Carli20155903,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {A decentralized resource allocation approach for sharing renewable energy among interconnected smart homes},
  year = {2015},
  journal = {Proceedings of the IEEE Conference on Decision and Control},
  volume = {54rd IEEE Conference on Decision and Control,CDC 2015},
  pages = {5903 – 5908},
  doi = {10.1109/CDC.2015.7403147},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962024908&doi=10.1109%2fCDC.2015.7403147&partnerID=40&md5=194027b41fd3ace430f8f40254ace4de},
  abstract = {The paper deals with the scheduling of energy activities of a group of interconnected users that buy energy from a producer and share a renewable energy source. The scheduling problem is stated and solved with a twofold goal. First, the model is formulated to ensure social welfare-optimal allocation of the energy produced from the shared renewable energy generator. Second, the model aims at cost-optimal planning of users' controllable appliances taking into account a realistic time-varying quadratic pricing of the energy bought from the distribution network. The solution approach relies on a decentralized optimization algorithm that is composed by a two-level iterative procedure combining Gauss-Seidel decomposition with competitive game formulation. A case study simulated in different scenarios demonstrates that the approach allows exploiting the potential of renewable energy sources' sharing to reduce individual users' energy consumption costs, limiting the peak average ratio of energy profiles and complying with the customer's energy needs. © 2015 IEEE.},
  author_keywords = {Energy consumption; Games; Home appliances; Optimization; Pricing; Renewable energy sources; Resource management},
  keywords = {Automation; Costs; Domestic appliances; Economics; Energy utilization; Intelligent buildings; Iterative methods; Natural resources; Optimization; Resource allocation; Scheduling; Decentralized optimization; Decentralized resource allocation; Games; Optimal allocation; Renewable energies; Renewable energy generators; Renewable energy source; Resource management; Renewable energy resources},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 37}
  }

• Piconese, A., Bourdeaud’Huy, T., Dotoli, M. & Hammadi, S. (2015) A mathematical programming model for the real time traffic management of railway networks under disturbances. IN Communications in Computer and Information Science, 509.215 – 234. doi:10.1007/978-3-319-17509-6_15
  [BibTeX] [Abstract] [Download PDF]

  The real-time traffic management allows to solve unexpected disturbances that occur along a railway line during the normal development of the traffic. After a disturbance, the original timetable is restored through the rescheduling process. Despite the improvements of off-line decision support tools for trains dispatchers that enable a better use of rail infrastructure, real-time traffic management received a limited scientific attention. In this paper, we deal with the real time traffic management for regional railway networks, mainly single tracked, in which a centralized traffic control system is installed. The rescheduling problem is presented as a Mixed Integer Linear Programming Model which resolution allows to carry out the rescheduling process in a very short computational time. © Springer International Publishing Switzerland 2015.

  @ARTICLE{Piconese2015215,
  author = {Piconese, Astrid and Bourdeaud’Huy, Thomas and Dotoli, Mariagrazia and Hammadi, Slim},
  title = {A mathematical programming model for the real time traffic management of railway networks under disturbances},
  year = {2015},
  journal = {Communications in Computer and Information Science},
  volume = {509},
  pages = {215 – 234},
  doi = {10.1007/978-3-319-17509-6_15},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929650069&doi=10.1007%2f978-3-319-17509-6_15&partnerID=40&md5=dd152439a8b3d9703f8defaeba394970},
  abstract = {The real-time traffic management allows to solve unexpected disturbances that occur along a railway line during the normal development of the traffic. After a disturbance, the original timetable is restored through the rescheduling process. Despite the improvements of off-line decision support tools for trains dispatchers that enable a better use of rail infrastructure, real-time traffic management received a limited scientific attention. In this paper, we deal with the real time traffic management for regional railway networks, mainly single tracked, in which a centralized traffic control system is installed. The rescheduling problem is presented as a Mixed Integer Linear Programming Model which resolution allows to carry out the rescheduling process in a very short computational time. © Springer International Publishing Switzerland 2015.},
  author_keywords = {Centralized traffic control; Mixed Integer Linear Programming; Railway systems; Real-time optimization; Regional networks; Single-tracked},
  keywords = {Decision support systems; Integer programming; Mathematical programming; Operations research; Railroads; Rails; Real time systems; Traffic control; Transportation; Centralized traffic controls; Mixed integer linear programming; Railway system; Real-time optimization; Regional networks; Single-tracked; Railroad transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Bevilacqua, V., Carnimeo, L., Guccione, P., Mastronardi, G., Uva, A. E., Fiorentino, M., Monno, G., Marino, F., Dotoli, M., Costantino, N., Dassisti, M. & Carbonara, N. (2015) A multimodal system for nonverbal human feature recognition in emotional framework IN ACM International Conference Proceeding Series., 19 – 24. doi:10.1145/2809643.2809645
  [BibTeX] [Abstract] [Download PDF]

  A correct recognition of nonverbal expressions is currently one of the most important challenges of research in the field of human computer interaction. The ability to recognize human actions could change the way to interact with machines in several environments and contexts, or even the way to live. In this paper, we describe the advances of a previous study finalized to design, implement and validate an innovative recognition system already developed by some of the authors. It was aimed at recognizing two opposite emotional conditions (resonance and dissonance) of a candidate to a job position interacting with the recruiter during a job interview. Results in terms of the accuracy, resonance rate, and dissonance rate of the three new optimized neural networkbased (NN) classifiers are discussed. Comparison with previous results of three NN classifiers is also presented based on three single domains: facial, vocal and gestural. © 2015 held by the owner/author(s).

  @CONFERENCE{Bevilacqua201519,
  author = {Bevilacqua, Vitoantonio and Carnimeo, Leonarda and Guccione, Pietro and Mastronardi, Giuseppe and Uva, Antonio Emanuele and Fiorentino, Michele and Monno, Giuseppe and Marino, Francescomaria and Dotoli, Mariagrazia and Costantino, Nicola and Dassisti, Michele and Carbonara, Nunzia},
  title = {A multimodal system for nonverbal human feature recognition in emotional framework},
  year = {2015},
  journal = {ACM International Conference Proceeding Series},
  volume = {2015-September},
  pages = {19 – 24},
  doi = {10.1145/2809643.2809645},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84947423101&doi=10.1145%2f2809643.2809645&partnerID=40&md5=72e90f3bd43f54d629785ef122ef80e8},
  abstract = {A correct recognition of nonverbal expressions is currently one of the most important challenges of research in the field of human computer interaction. The ability to recognize human actions could change the way to interact with machines in several environments and contexts, or even the way to live. In this paper, we describe the advances of a previous study finalized to design, implement and validate an innovative recognition system already developed by some of the authors. It was aimed at recognizing two opposite emotional conditions (resonance and dissonance) of a candidate to a job position interacting with the recruiter during a job interview. Results in terms of the accuracy, resonance rate, and dissonance rate of the three new optimized neural networkbased (NN) classifiers are discussed. Comparison with previous results of three NN classifiers is also presented based on three single domains: facial, vocal and gestural. © 2015 held by the owner/author(s).},
  author_keywords = {Facial/vocal/gestural features; Job interview; Neural networks and support vector machines; Nonverbal emotional recognition},
  keywords = {Neural networks; Support vector machines; Emotional recognition; Facial/vocal/gestural features; Feature recognition; Job interviews; Multimodal system; Non-verbal human; Recognition systems; Single domains; Human computer interaction},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Carli, R., Dotoli, M., Pellegrino, R. & Ranieri, L. (2015) Using multi-objective optimization for the integrated energy efficiency improvement of a smart city public buildings’ portfolio IN IEEE International Conference on Automation Science and Engineering., 21 – 26. doi:10.1109/CoASE.2015.7294035
  [BibTeX] [Abstract] [Download PDF]

  The paper presents a multi-objective optimization algorithm to improve in an integrated and holistic way the building stock energy efficiency, sustainability, and comfort, while efficiently allocating the available budget to the buildings. The developed algorithm determines a set of optimal energy retrofit plans for a portfolio of public buildings in a smart city. An existing stock of public buildings located in the municipality of Bari, Italy is used as case study. The application results demonstrate that the developed algorithm is an effective support tool for the smart city governance in enhancing the energy efficiency performance of a stock of public buildings. © 2015 IEEE.

  @CONFERENCE{Carli201521,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Pellegrino, Roberta and Ranieri, Luigi},
  title = {Using multi-objective optimization for the integrated energy efficiency improvement of a smart city public buildings' portfolio},
  year = {2015},
  journal = {IEEE International Conference on Automation Science and Engineering},
  volume = {2015-October},
  pages = {21 – 26},
  doi = {10.1109/CoASE.2015.7294035},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952780524&doi=10.1109%2fCoASE.2015.7294035&partnerID=40&md5=64470489d4914a6d949700900aa47d44},
  abstract = {The paper presents a multi-objective optimization algorithm to improve in an integrated and holistic way the building stock energy efficiency, sustainability, and comfort, while efficiently allocating the available budget to the buildings. The developed algorithm determines a set of optimal energy retrofit plans for a portfolio of public buildings in a smart city. An existing stock of public buildings located in the municipality of Bari, Italy is used as case study. The application results demonstrate that the developed algorithm is an effective support tool for the smart city governance in enhancing the energy efficiency performance of a stock of public buildings. © 2015 IEEE.},
  keywords = {Algorithms; Automation; Budget control; Buildings; Multiobjective optimization; Optimization; Building stocks; Energy efficiency improvements; Optimal energy; Public buildings; Smart cities; Support tool; Energy efficiency},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 31}
  }

• Carli, R., Dotoli, M. & Pellegrino, R. (2015) ICT and optimization for the energy management of smart cities: The street lighting decision panel IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA.. doi:10.1109/ETFA.2015.7301435
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the emerging need for tools devoted to the energy governance of smart cities. We propose a hierarchical decision process that supports the energy manager in governing the smart city while addressing different urban sectors with an integrated, structured, and transparent planning. Starting from the urban control center proposed in a previous contribution for the urban energy management, a hierarchical strategic decision structure is proposed. More in detail, a two-level decentralized programming model integrates several decision making units (decision panels), each focusing on the energy optimization of a specific urban subsystem. We focus on the presentation of the street lighting decision panel and on its application to the energy management of the public lighting of the city of Bari (Italy), where a smart city program has recently been launched. © 2015 IEEE.

  @CONFERENCE{Carli2015,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Pellegrino, Roberta},
  title = {ICT and optimization for the energy management of smart cities: The street lighting decision panel},
  year = {2015},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  volume = {2015-October},
  doi = {10.1109/ETFA.2015.7301435},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952882893&doi=10.1109%2fETFA.2015.7301435&partnerID=40&md5=012ab885ea35346c5c280804295955c9},
  abstract = {The paper addresses the emerging need for tools devoted to the energy governance of smart cities. We propose a hierarchical decision process that supports the energy manager in governing the smart city while addressing different urban sectors with an integrated, structured, and transparent planning. Starting from the urban control center proposed in a previous contribution for the urban energy management, a hierarchical strategic decision structure is proposed. More in detail, a two-level decentralized programming model integrates several decision making units (decision panels), each focusing on the energy optimization of a specific urban subsystem. We focus on the presentation of the street lighting decision panel and on its application to the energy management of the public lighting of the city of Bari (Italy), where a smart city program has recently been launched. © 2015 IEEE.},
  author_keywords = {Cities and towns; Decision making; Lighting; Optimization; Smart cities},
  keywords = {Application programs; Energy management; Factory automation; Lighting; Optimization; Street lighting; Cities and towns; Decision making unit; Energy optimization; Hierarchical decisions; ITS applications; Programming models; Smart cities; Strategic decisions; Decision making},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 19}
  }

• Dotoli, M., Epicoco, N. & Falagario, M. (2015) A Technique for Supply Chain Network Design under Uncertainty using Cross-Efficiency Fuzzy Data Envelopment Analysis IN IFAC-PapersOnLine., 634 – 639. doi:10.1016/j.ifacol.2015.06.153
  [BibTeX] [Abstract] [Download PDF]

  The paper focuses on Supply Chain Network Design (SCND) under uncertainty. We propose a SCND method extending an approach originally proposed by some of the authors for supplier ranking. The novel method integrates the cross-efficiency Data Envelopment Analysis (DEA) and fuzzy set theory to manage the SCND problem considering nondeterministic input and output data. After ranking all the actors belonging to each SCN stage, a linear integer programming model is stated and solved for each pair of subsequent SC stages to maximize the overall SCN efficiency, while respecting the available capacity at each node and satisfying customers’ demand. A case study is presented to show the technique effectiveness. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

  @CONFERENCE{Dotoli2015634,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco},
  title = {A Technique for Supply Chain Network Design under Uncertainty using Cross-Efficiency Fuzzy Data Envelopment Analysis},
  year = {2015},
  journal = {IFAC-PapersOnLine},
  volume = {48},
  number = {3},
  pages = {634 – 639},
  doi = {10.1016/j.ifacol.2015.06.153},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953877988&doi=10.1016%2fj.ifacol.2015.06.153&partnerID=40&md5=80301c5e693bc3b2946766f9b7165674},
  abstract = {The paper focuses on Supply Chain Network Design (SCND) under uncertainty. We propose a SCND method extending an approach originally proposed by some of the authors for supplier ranking. The novel method integrates the cross-efficiency Data Envelopment Analysis (DEA) and fuzzy set theory to manage the SCND problem considering nondeterministic input and output data. After ranking all the actors belonging to each SCN stage, a linear integer programming model is stated and solved for each pair of subsequent SC stages to maximize the overall SCN efficiency, while respecting the available capacity at each node and satisfying customers' demand. A case study is presented to show the technique effectiveness. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},
  author_keywords = {cross-efficiency; data envelopment analysis; fuzzy logic; supply chain network design; uncertainty},
  keywords = {Data envelopment analysis; Efficiency; Fuzzy set theory; Integer programming; Supply chains; Uncertainty analysis; Available capacity; Cross efficiency; Fuzzy data envelopment analysis; Input and outputs; Linear integer programming; Supply chain network design; uncertainty; Fuzzy logic},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 12; All Open Access, Gold Open Access}
  }

2014

• Cabasino, M. P., Dotoli, M. & Seatzu, C. (2014) Modelling manufacturing systems with place/transition nets and timed petri nets .
  [BibTeX] [Abstract] [Download PDF]

  Manufacturing systems are man-made systems that are increasingly used in factory automation since they can manufacture products with a high degree of automation and numerous different specifications. Manufacturing systems may be defined as discrete production systems in which the handled materials are discrete entities, for example, parts that are machined or assembled [35]. As a result, discrete event formalisms are particularly suitable for modelling manufacturing systems using the basic concepts of events and activities. Hence, manufacturing systems can be effectively represented as discrete event systems (DESs), whose dynamics depends on the interaction of asynchronous discrete events, such as the arrival or departure of parts or products in a buffer, the start of an operation, the completion of a task and the failure of a machine. Among the numerous DES frameworks, 4 Petri Nets (PNs) are a family of formalisms that allow to effectively model manufacturing systems. Indeed, PNs are a graphical and mathematical tool that provides a uniform environment for the design, modelling, formal analysis and performance evaluation of DES. Typically, manufacturing systems are modelled in the PN formalism such that resources (machines, automated guided vehicles (AGVs, buffers, etc.) are represented by places. The corresponding marking represents the capacity of the resource, while the absence of tokens indicates that the resource is unavailable. Therefore, places are useful to capture the decentralized nature of the system and the distributed state of the information in a complex manufacturing system. More generally, places represent conditions in the operation of the system. For instance, a marked (unmarked) place may represent the fact that a machine is operative (down). Moreover, transitions typically represent the start or the termination of an event. Hence, places and transitions represent conditions and precedence relations for the occurrence of events driving the manufacturing system dynamics. In the related literature, PNs contribute in a major way to the modelling of manufacturing systems because they include numerous different formalisms sharing basic principles in a consistent way, each best suited for the desired specific purpose or degree of detail. © 2014 by Taylor & Francis Group, LLC.

  @BOOK{Cabasino20143,
  author = {Cabasino, Maria Paola and Dotoli, Mariagrazia and Seatzu, Carla},
  title = {Modelling manufacturing systems with place/transition nets and timed petri nets},
  year = {2014},
  journal = {Formal Methods in Manufacturing},
  pages = {3 – 28},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055390442&partnerID=40&md5=afdabd62eae23f7af588b12245ed5908},
  abstract = {Manufacturing systems are man-made systems that are increasingly used in factory automation since they can manufacture products with a high degree of automation and numerous different specifications. Manufacturing systems may be defined as discrete production systems in which the handled materials are discrete entities, for example, parts that are machined or assembled [35]. As a result, discrete event formalisms are particularly suitable for modelling manufacturing systems using the basic concepts of events and activities. Hence, manufacturing systems can be effectively represented as discrete event systems (DESs), whose dynamics depends on the interaction of asynchronous discrete events, such as the arrival or departure of parts or products in a buffer, the start of an operation, the completion of a task and the failure of a machine. Among the numerous DES frameworks, 4 Petri Nets (PNs) are a family of formalisms that allow to effectively model manufacturing systems. Indeed, PNs are a graphical and mathematical tool that provides a uniform environment for the design, modelling, formal analysis and performance evaluation of DES. Typically, manufacturing systems are modelled in the PN formalism such that resources (machines, automated guided vehicles (AGVs, buffers, etc.) are represented by places. The corresponding marking represents the capacity of the resource, while the absence of tokens indicates that the resource is unavailable. Therefore, places are useful to capture the decentralized nature of the system and the distributed state of the information in a complex manufacturing system. More generally, places represent conditions in the operation of the system. For instance, a marked (unmarked) place may represent the fact that a machine is operative (down). Moreover, transitions typically represent the start or the termination of an event. Hence, places and transitions represent conditions and precedence relations for the occurrence of events driving the manufacturing system dynamics. In the related literature, PNs contribute in a major way to the modelling of manufacturing systems because they include numerous different formalisms sharing basic principles in a consistent way, each best suited for the desired specific purpose or degree of detail. © 2014 by Taylor & Francis Group, LLC.},
  keywords = {Automatic guided vehicles; Automobile manufacture; Factory automation; Petri nets; Automated guided vehicles; Complex manufacturing systems; Degree of automation; Discrete event formalisms; Discrete production; Mathematical tools; Performance evaluations; Precedence relations; Discrete event simulation},
  type = {Book chapter},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Dotoli, M., Epicoco, N., Turchiano, B., Falagario, M. & Sciancalepore, F. (2014) Simulation and evaluation of the auction based day ahead energy market via a Nash equilibrium model and zonal pricing IN 2014 22nd Mediterranean Conference on Control and Automation, MED 2014., 1061 – 1066. doi:10.1109/MED.2014.6961515
  [BibTeX] [Abstract] [Download PDF]

  We present a simulation model based on the Nash equilibrium for the analysis of the auction based day ahead electricity generation market. Starting from the empirical data distributions of the market clearing price and the energy demand registered by the supervisory authority, the model allows evaluating the market competitiveness and preventing anticompetitive actions by participants. It also represents a basis for a decision support tool for producers to define their optimal bidding strategy. With respect to other existing models, it allows considering differences in the generation capacities of producers, in the utilized energy sources, and in the zonal market. The model is tested in the Italian energy market by means of two different scenarios and by varying the number of bidders and their production capacities. © 2014 IEEE.

  @CONFERENCE{Dotoli20141061,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Turchiano, Biagio and Falagario, Marco and Sciancalepore, Fabio},
  title = {Simulation and evaluation of the auction based day ahead energy market via a Nash equilibrium model and zonal pricing},
  year = {2014},
  journal = {2014 22nd Mediterranean Conference on Control and Automation, MED 2014},
  pages = {1061 – 1066},
  doi = {10.1109/MED.2014.6961515},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84916888779&doi=10.1109%2fMED.2014.6961515&partnerID=40&md5=96eaf43cc7d748f4979f1e745df559bb},
  abstract = {We present a simulation model based on the Nash equilibrium for the analysis of the auction based day ahead electricity generation market. Starting from the empirical data distributions of the market clearing price and the energy demand registered by the supervisory authority, the model allows evaluating the market competitiveness and preventing anticompetitive actions by participants. It also represents a basis for a decision support tool for producers to define their optimal bidding strategy. With respect to other existing models, it allows considering differences in the generation capacities of producers, in the utilized energy sources, and in the zonal market. The model is tested in the Italian energy market by means of two different scenarios and by varying the number of bidders and their production capacities. © 2014 IEEE.},
  author_keywords = {auction; competitiveness; electricity market; game theory; generation companies; Nash equilibrium; simulation},
  keywords = {Competition; Computation theory; Costs; Decision support systems; Game theory; auction; competitiveness; Generation companies; Nash equilibria; simulation; Power markets},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Carli, R. & Dotoli, M. (2014) Energy scheduling of a smart home under nonlinear pricing IN Proceedings of the IEEE Conference on Decision and Control., 5648 – 5653. doi:10.1109/CDC.2014.7040273
  [BibTeX] [Abstract] [Download PDF]

  The paper focuses on the scheduling of energy activities in smart homes equipped with controllable electrical appliances, renewable energy sources, dispatchable energy generators, and energy storage systems. We formulate a mixed integer quadratic programming energy scheduling algorithm for cost minimization under nonlinear pricing. The scheduling technique manages the use of electrical appliances, plans the energy production and supplying, and programs the storage systems charging/discharging. A case study simulated in different scenarios demonstrates that the approach allows full exploitation of the potential of local energy generation and storage to reduce the individual user energy consumption costs, while complying with the customer energy needs. © 2014 IEEE.

  @CONFERENCE{Carli20145648,
  author = {Carli, Raffaele and Dotoli, Mariagrazia},
  title = {Energy scheduling of a smart home under nonlinear pricing},
  year = {2014},
  journal = {Proceedings of the IEEE Conference on Decision and Control},
  volume = {2015-February},
  number = {February},
  pages = {5648 – 5653},
  doi = {10.1109/CDC.2014.7040273},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961994657&doi=10.1109%2fCDC.2014.7040273&partnerID=40&md5=55539508a30611826d5d2e0f0b11c853},
  abstract = {The paper focuses on the scheduling of energy activities in smart homes equipped with controllable electrical appliances, renewable energy sources, dispatchable energy generators, and energy storage systems. We formulate a mixed integer quadratic programming energy scheduling algorithm for cost minimization under nonlinear pricing. The scheduling technique manages the use of electrical appliances, plans the energy production and supplying, and programs the storage systems charging/discharging. A case study simulated in different scenarios demonstrates that the approach allows full exploitation of the potential of local energy generation and storage to reduce the individual user energy consumption costs, while complying with the customer energy needs. © 2014 IEEE.},
  keywords = {Automation; Costs; Energy utilization; Integer programming; Intelligent buildings; Quadratic programming; Renewable energy resources; Scheduling; Dispatchable energies; Electrical appliances; Energy productions; Energy storage systems; Mixed integer quadratic programming; Non-linear pricing; Renewable energy source; Scheduling techniques; Scheduling algorithms},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 42}
  }

• Dotoli, M., Epicoco, N., Falagario, M. & Cavone, G. (2014) A timed Petri nets model for intermodal freight transport terminals IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 176 – 181. doi:10.3182/20140514-3-FR-4046.00038
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a general modelling framework for intermodal freight transport terminals. The model allows evaluating the operational performance of such transportation systems, assessing the efficiency level of the terminal and identifying its bottlenecks by suitable performance indices. Moreover, it allows evaluating different solutions to the identified criticalities. The proposed framework is modular and based on timed Petri nets: places represent resources and capacities or conditions, transitions model inputs, flows and activities into the terminal, and tokens are intermodal transport units or the means on which they are transported. A simulation of a case study shows the model effectiveness. © IFAC.

  @CONFERENCE{Dotoli2014176,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Cavone, Graziana},
  title = {A timed Petri nets model for intermodal freight transport terminals},
  year = {2014},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {9},
  number = {3},
  pages = {176 – 181},
  doi = {10.3182/20140514-3-FR-4046.00038},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84945963822&doi=10.3182%2f20140514-3-FR-4046.00038&partnerID=40&md5=12d63035451f5fdd5d932509425ee237},
  abstract = {This paper presents a general modelling framework for intermodal freight transport terminals. The model allows evaluating the operational performance of such transportation systems, assessing the efficiency level of the terminal and identifying its bottlenecks by suitable performance indices. Moreover, it allows evaluating different solutions to the identified criticalities. The proposed framework is modular and based on timed Petri nets: places represent resources and capacities or conditions, transitions model inputs, flows and activities into the terminal, and tokens are intermodal transport units or the means on which they are transported. A simulation of a case study shows the model effectiveness. © IFAC.},
  author_keywords = {Discrete event systems; Intermodal transport; Modelling; Simulation; Timed Petri nets},
  keywords = {Freight transportation; Intermodal transportation; Models; Petri nets; Traffic control; Intermodal freight transport; Intermodal transport; Modelling framework; Operational performance; Simulation; Timed Petri Net; Timed Petri nets models; Transportation system; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 19; All Open Access, Bronze Open Access}
  }

• Dotoli, M., Epicoco, N., Falagario, M., Seatzu, C. & Turchiano, B. (2014) Optimization of intermodal rail-road freight transport terminals IN Proceedings – IEEE International Conference on Robotics and Automation., 1971 – 1976. doi:10.1109/ICRA.2014.6907120
  [BibTeX] [Abstract] [Download PDF]

  In this paper we present a decision support scheme to help managing and optimizing two critical activities in intermodal terminals, namely the containers allocation in the terminal yard and the freight trains composition. In particular, the focus of this paper is on the first problem and the goal is that of maximizing the utilization of the available space while keeping into account several constraints. The approach was successfully tested on a real case study, the rail-road terminal of a leading intermodal logistics company. © 2014 IEEE.

  @CONFERENCE{Dotoli20141971,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Seatzu, Carla and Turchiano, Biagio},
  title = {Optimization of intermodal rail-road freight transport terminals},
  year = {2014},
  journal = {Proceedings - IEEE International Conference on Robotics and Automation},
  pages = {1971 – 1976},
  doi = {10.1109/ICRA.2014.6907120},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929208527&doi=10.1109%2fICRA.2014.6907120&partnerID=40&md5=92706f4392f3bb5e46ee05561f09136c},
  abstract = {In this paper we present a decision support scheme to help managing and optimizing two critical activities in intermodal terminals, namely the containers allocation in the terminal yard and the freight trains composition. In particular, the focus of this paper is on the first problem and the goal is that of maximizing the utilization of the available space while keeping into account several constraints. The approach was successfully tested on a real case study, the rail-road terminal of a leading intermodal logistics company. © 2014 IEEE.},
  keywords = {Decision support systems; Railroads; Roads and streets; Critical activities; Decision supports; Freight trains; Intermodal terminals; Logistics company; Rail-road terminals; Real case; Freight transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Bevilacqua, V., Dotoli, M., Foglia, M. M., Acciani, F., Tattoli, G. & Valori, M. (2014) Artificial neural networks for feedback control of a human elbow hydraulic prosthesis. IN Neurocomputing, 137.3 – 11. doi:10.1016/j.neucom.2013.05.066
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses feedback control of actuated prostheses based on the Stewart platform parallel mechanism. In such a problem it is essential to apply a feasible numerical method to determine in real time the solution of the forward kinematics, which is highly nonlinear and characterized by analytical indetermination. In this paper, the forward kinematics problem for a human elbow hydraulic prosthesis developed by the research group of Polytechnic of Bari is solved using artificial neural networks as an effective and simple method to obtain in real time the solution of the problem while limiting the computational effort. We show the effectiveness of the technique by designing a PID controller that governs the arm motion thanks to the provided neural computation of the forward kinematics. © 2014 Elsevier B.V.

  @ARTICLE{Bevilacqua20143,
  author = {Bevilacqua, Vitoantonio and Dotoli, Mariagrazia and Foglia, Mario Massimo and Acciani, Francesco and Tattoli, Giacomo and Valori, Marcello},
  title = {Artificial neural networks for feedback control of a human elbow hydraulic prosthesis},
  year = {2014},
  journal = {Neurocomputing},
  volume = {137},
  pages = {3 – 11},
  doi = {10.1016/j.neucom.2013.05.066},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84899638087&doi=10.1016%2fj.neucom.2013.05.066&partnerID=40&md5=d9d0dcfdb1b0874d1405ce613f59dcf7},
  abstract = {The paper addresses feedback control of actuated prostheses based on the Stewart platform parallel mechanism. In such a problem it is essential to apply a feasible numerical method to determine in real time the solution of the forward kinematics, which is highly nonlinear and characterized by analytical indetermination. In this paper, the forward kinematics problem for a human elbow hydraulic prosthesis developed by the research group of Polytechnic of Bari is solved using artificial neural networks as an effective and simple method to obtain in real time the solution of the problem while limiting the computational effort. We show the effectiveness of the technique by designing a PID controller that governs the arm motion thanks to the provided neural computation of the forward kinematics. © 2014 Elsevier B.V.},
  author_keywords = {Artificial neural networks; Control; Forward kinematics; Human prosthesis; Parallel mechanism; Simulation},
  keywords = {Control; Feedback control; Mechanisms; Neural networks; Simulators; Computational effort; Forward kinematics; Forward kinematics problem; Neural computations; Parallel mechanisms; Research groups; Simulation; Stewart platforms; Prosthetics},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 13}
  }

• Piconese, A., Bourdeaud’Huy, T., Dotoli, M. & Hammadi, S. (2014) A revisited model for the real time traffic management IN ICORES 2014 – Proceedings of the 3rd International Conference on Operations Research and Enterprise Systems., 139 – 150. doi:10.5220/0004869701390150
  [BibTeX] [Abstract] [Download PDF]

  The real-time trafficmanagement allow to solve unexpected disturbances that occur along a railway line during the normal developement of the traffic. The original timetable is restored through the rescheduling process. Despite the increase of real-time decision support tools for trains dispatchers that enable a better use of rail infrastructure, real-time traffic management received a limited scientific attention. In this paper, we deal with the real time traffic management for regional railway networks, mainly single tracks, in which a centralized traffic control system is installed. The rescheduling problem is presented as a Mixed Integer Linear Programming Model which resolution allows to carry out the rescheduling process in a very short computational time. Copyright © 2014 SCITEPRESS.

  @CONFERENCE{Piconese2014139,
  author = {Piconese, Astrid and Bourdeaud'Huy, Thomas and Dotoli, Mariagrazia and Hammadi, Slim},
  title = {A revisited model for the real time traffic management},
  year = {2014},
  journal = {ICORES 2014 - Proceedings of the 3rd International Conference on Operations Research and Enterprise Systems},
  pages = {139 – 150},
  doi = {10.5220/0004869701390150},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902323935&doi=10.5220%2f0004869701390150&partnerID=40&md5=b88d465e7539a31f982d85adced9347d},
  abstract = {The real-time trafficmanagement allow to solve unexpected disturbances that occur along a railway line during the normal developement of the traffic. The original timetable is restored through the rescheduling process. Despite the increase of real-time decision support tools for trains dispatchers that enable a better use of rail infrastructure, real-time traffic management received a limited scientific attention. In this paper, we deal with the real time traffic management for regional railway networks, mainly single tracks, in which a centralized traffic control system is installed. The rescheduling problem is presented as a Mixed Integer Linear Programming Model which resolution allows to carry out the rescheduling process in a very short computational time. Copyright © 2014 SCITEPRESS.},
  author_keywords = {Centralized traffic control; Linear programming; Railway systems; Real-time optimization; Regional networks; Single-track},
  keywords = {Decision support systems; Integer programming; Linear programming; Operations research; Railroad transportation; Railroads; Rails; Traffic control; Centralized traffic controls; Railway system; Real-time optimization; Regional networks; Single-tracks; Real time systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Hybrid Gold Open Access}
  }

• Dotoli, M., Epicoco, N., Cavone, G., Turchiano, B. & Falagario, M. (2014) Simulation and performance evaluation of an Intermodal terminal using Petri Nets IN Proceedings – 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014., 327 – 332. doi:10.1109/CoDIT.2014.6996915
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on modelling and performance evaluation of an Intermodal Freight Transport Terminal (IFTT), the rail-road inland terminal of a leading Italian intermodal logistics company. The IFTT is regarded as a discrete event system and is modelled in a timed Petri net framework. By means of suitable performance indices, we simulate the Petri net model and evaluate the operational performance of the transport system. This allows assessing the efficiency level of the terminal and identifying its criticalities and bottlenecks. Further, the model allows evaluating different solutions to the recognized criticalities under alternative scenarios (e.g., when inflow traffic increases and congestions may occur). © 2014 IEEE.

  @CONFERENCE{Dotoli2014327,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Cavone, Graziana and Turchiano, Biagio and Falagario, Marco},
  title = {Simulation and performance evaluation of an Intermodal terminal using Petri Nets},
  year = {2014},
  journal = {Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014},
  pages = {327 – 332},
  doi = {10.1109/CoDIT.2014.6996915},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921395897&doi=10.1109%2fCoDIT.2014.6996915&partnerID=40&md5=fd846395d6e7004b94407b51c1ec4da3},
  abstract = {This paper focuses on modelling and performance evaluation of an Intermodal Freight Transport Terminal (IFTT), the rail-road inland terminal of a leading Italian intermodal logistics company. The IFTT is regarded as a discrete event system and is modelled in a timed Petri net framework. By means of suitable performance indices, we simulate the Petri net model and evaluate the operational performance of the transport system. This allows assessing the efficiency level of the terminal and identifying its criticalities and bottlenecks. Further, the model allows evaluating different solutions to the recognized criticalities under alternative scenarios (e.g., when inflow traffic increases and congestions may occur). © 2014 IEEE.},
  author_keywords = {Discrete event systems; Intermodal transport terminal; Modelling; Performance evaluation; Simulation; Timed Petri nets},
  keywords = {Criticality (nuclear fission); Freight transportation; Intermodal transportation; Models; Petri nets; Traffic control; Intermodal freight transport; Intermodal terminals; Intermodal transport; Operational performance; Performance evaluation; Performance indices; Simulation; Timed Petri Net; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Carli, R., Deidda, P., Dotoli, M. & Pellegrino, R. (2014) An urban control center for the energy governance of a smart city IN 19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014.. doi:10.1109/ETFA.2014.7005155
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the emerging need of providing urban managers with tools for energy governance of smart cities. We present the architecture of a decision support system called Urban Control Center (UCC). The UCC measures the city energy performance and supports the decision maker in determining the optimal action plan for implementing smartness strategies in the city energy governance. To this aim, the UCC relies on a two-level decentralized programming model that integrates several decision making units (decision panels), each focusing on the energy optimization of a specific urban subsystem. © 2014 IEEE.

  @CONFERENCE{Carli2014,
  author = {Carli, Raffaele and Deidda, Paolo and Dotoli, Mariagrazia and Pellegrino, Roberta},
  title = {An urban control center for the energy governance of a smart city},
  year = {2014},
  journal = {19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014},
  doi = {10.1109/ETFA.2014.7005155},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946686880&doi=10.1109%2fETFA.2014.7005155&partnerID=40&md5=7ae375bfea52c5c6212722aca93bc04d},
  abstract = {The paper addresses the emerging need of providing urban managers with tools for energy governance of smart cities. We present the architecture of a decision support system called Urban Control Center (UCC). The UCC measures the city energy performance and supports the decision maker in determining the optimal action plan for implementing smartness strategies in the city energy governance. To this aim, the UCC relies on a two-level decentralized programming model that integrates several decision making units (decision panels), each focusing on the energy optimization of a specific urban subsystem. © 2014 IEEE.},
  keywords = {Artificial intelligence; Decision support systems; Factory automation; Control center; Decision makers; Decision making unit; Energy optimization; Energy performance; Optimal actions; Programming models; Smart cities; Decision making},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 14}
  }

• Dotoli, M., Epicoco, N., Falagario, M., Sciancalepore, F. & Costantino, N. (2014) A Nash equilibrium simulation model for the competitiveness evaluation of the auction based day ahead electricity market. IN Computers in Industry, 65.774 – 785. doi:10.1016/j.compind.2014.02.014
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a simulation model based on the Nash equilibrium notion for the auction based day ahead electricity generation market. The presented model enhances a previous formalism proposed in the related literature by employing empirical data distributions of the market clearing price as registered by the market authority (e.g. the Independent System Operator). The model is effective when power suppliers with different generation capacities are considered, differently from the starting model that unrealistically assumes equal capacities. The proposed approach aims at evaluating the electricity market competitiveness with regard to the bidder strategies in order to prevent their anticompetitive actions. The framework is applied to a real data set regarding the Italian electricity market to enlighten its effectiveness in different scenarios, varying the number and capacity of participating bidders. The model can be employed as a basis for a decision support tool both for market participants (to define their optimal bidding strategy) and regulators (to avoid collusive strategies). © 2014 Elsevier B.V.

  @ARTICLE{Dotoli2014774,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Sciancalepore, Fabio and Costantino, Nicola},
  title = {A Nash equilibrium simulation model for the competitiveness evaluation of the auction based day ahead electricity market},
  year = {2014},
  journal = {Computers in Industry},
  volume = {65},
  number = {4},
  pages = {774 – 785},
  doi = {10.1016/j.compind.2014.02.014},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84897413926&doi=10.1016%2fj.compind.2014.02.014&partnerID=40&md5=d05586a0a1e5f5199249321a07505bc7},
  abstract = {This paper presents a simulation model based on the Nash equilibrium notion for the auction based day ahead electricity generation market. The presented model enhances a previous formalism proposed in the related literature by employing empirical data distributions of the market clearing price as registered by the market authority (e.g. the Independent System Operator). The model is effective when power suppliers with different generation capacities are considered, differently from the starting model that unrealistically assumes equal capacities. The proposed approach aims at evaluating the electricity market competitiveness with regard to the bidder strategies in order to prevent their anticompetitive actions. The framework is applied to a real data set regarding the Italian electricity market to enlighten its effectiveness in different scenarios, varying the number and capacity of participating bidders. The model can be employed as a basis for a decision support tool both for market participants (to define their optimal bidding strategy) and regulators (to avoid collusive strategies). © 2014 Elsevier B.V.},
  author_keywords = {Competitiveness; Electricity generation market; Market dynamics; Modelling; Nash equilibrium; Simulation},
  keywords = {Competition; Computation theory; Decision support systems; Electric industry; Electric power generation; Game theory; Models; Competitiveness; Electricity generation; Market dynamics; Nash equilibria; Simulation; Power markets},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 17}
  }

• Dotoli, M., Epicoco, N., Falagario, M., Turchiano, B., Cavone, G. & Convertini, A. (2014) A Decision Support System for real-time rescheduling of railways IN 2014 European Control Conference, ECC 2014., 696 – 701. doi:10.1109/ECC.2014.6862177
  [BibTeX] [Abstract] [Download PDF]

  We present a Decision Support System (DSS) for real-time management of railway networks. The DSS employs a mathematical programming approach addressing traffic rescheduling under unexpected disturbances in a mixed-(single- and double-) tracked network. The DSS simulates the network behavior with the mathematical programming model based on the railway topology and constraints, rescheduling the timetable in real time, detecting and solving conflicts in the network. The DSS is applied to a real data set related to a large portion of a regional network in Southern Italy. © 2014 EUCA.

  @CONFERENCE{Dotoli2014696,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Turchiano, Biagio and Cavone, Graziana and Convertini, Antonio},
  title = {A Decision Support System for real-time rescheduling of railways},
  year = {2014},
  journal = {2014 European Control Conference, ECC 2014},
  pages = {696 – 701},
  doi = {10.1109/ECC.2014.6862177},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911480266&doi=10.1109%2fECC.2014.6862177&partnerID=40&md5=1a944040060d3fed8ad9f768f452b52a},
  abstract = {We present a Decision Support System (DSS) for real-time management of railway networks. The DSS employs a mathematical programming approach addressing traffic rescheduling under unexpected disturbances in a mixed-(single- and double-) tracked network. The DSS simulates the network behavior with the mathematical programming model based on the railway topology and constraints, rescheduling the timetable in real time, detecting and solving conflicts in the network. The DSS is applied to a real data set related to a large portion of a regional network in Southern Italy. © 2014 EUCA.},
  keywords = {Mathematical programming; Railroad transportation; Railroads; Topology; Decision support system (dss); Mathematical programming models; Network behaviors; Railway network; Real data sets; Real-time management; Real-time rescheduling; Regional networks; Decision support systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 22}
  }

• Dotoli, M., Epicoco, N., Falagario, M. & Sciancalepore, F. (2014) Supplier evaluation and selection under uncertainty via an integrated model using cross-efficiency Data Envelopment Analysis and Monte Carlo simulation IN 19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014.. doi:10.1109/ETFA.2014.7005102
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses a key objective of the supply chain strategic design, i.e., the optimal selection of suppliers under uncertainty. A methodology integrating the cross-efficiency Data Envelopment Analysis and the Monte Carlo approach is proposed. Their combination allows overcoming the deterministic feature of the classical cross-efficiency DEA. Moreover, we define an indicator of the robustness of the determined supplier ranking. The resulting technique allows managing the supplier selection problem while considering nondeterministic input and output data, a significant circumstance for assessing potential suppliers, with which there are no previous commercial relationships. The approach helps buyers in choosing the right partners under uncertainty and ranking them upon a multiple sourcing strategy. © 2014 IEEE.

  @CONFERENCE{Dotoli2014,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Sciancalepore, Fabio},
  title = {Supplier evaluation and selection under uncertainty via an integrated model using cross-efficiency Data Envelopment Analysis and Monte Carlo simulation},
  year = {2014},
  journal = {19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014},
  doi = {10.1109/ETFA.2014.7005102},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983146247&doi=10.1109%2fETFA.2014.7005102&partnerID=40&md5=c5da4b3d399574a5e6fc8539516dbba6},
  abstract = {This paper addresses a key objective of the supply chain strategic design, i.e., the optimal selection of suppliers under uncertainty. A methodology integrating the cross-efficiency Data Envelopment Analysis and the Monte Carlo approach is proposed. Their combination allows overcoming the deterministic feature of the classical cross-efficiency DEA. Moreover, we define an indicator of the robustness of the determined supplier ranking. The resulting technique allows managing the supplier selection problem while considering nondeterministic input and output data, a significant circumstance for assessing potential suppliers, with which there are no previous commercial relationships. The approach helps buyers in choosing the right partners under uncertainty and ranking them upon a multiple sourcing strategy. © 2014 IEEE.},
  keywords = {Data envelopment analysis; Efficiency; Factory automation; Intelligent systems; Supply chains; Uncertainty analysis; Commercial relationship; Input and outputs; Integrated modeling; Monte Carlo approach; Optimal selection; Sourcing strategies; Supplier evaluation and selections; Supplier selection; Monte Carlo methods},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 4}
  }

• Danielis, R., Dotoli, M., Fanti, M. P., Mangini, A. M., Pesenti, R., Stecco, G. & Ukovich, W. (2014) Integrating ICT into Logistics Intermodal Systems: A petri net model of the Trieste port IN 2009 European Control Conference, ECC 2009., 4769 – 4774. doi:10.23919/ecc.2009.7075154
  [BibTeX] [Abstract] [Download PDF]

  The paper focuses on the issue of the modeling and management of Logistics Intermodal Systems (LIS) integrated by ICT (Information and Communication Technologies) tools. To this aim, we consider as a case study the port of Trieste (Italy) and we model the system in a Petri net framework. The port logistics and the truck traffic are described in different operative conditions characterized by different levels of ICT integration and information sharing between infrastructures and operators. Moreover, the system is simulated in the Matlab environment under different traffic scenarios and system capacity assumptions. The simulation results show that ICT have a huge potential for efficient real time management and operation of LIS. © 2009 EUCA.

  @CONFERENCE{Danielis20144769,
  author = {Danielis, Romeo and Dotoli, Mariagrazia and Fanti, Maria P. and Mangini, Agostino M. and Pesenti, Raffaele and Stecco, Gabriella and Ukovich, Walter},
  title = {Integrating ICT into Logistics Intermodal Systems: A petri net model of the Trieste port},
  year = {2014},
  journal = {2009 European Control Conference, ECC 2009},
  pages = {4769 – 4774},
  doi = {10.23919/ecc.2009.7075154},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84955199195&doi=10.23919%2fecc.2009.7075154&partnerID=40&md5=65f8221d56181b5a7bade81cb6eb5f82},
  abstract = {The paper focuses on the issue of the modeling and management of Logistics Intermodal Systems (LIS) integrated by ICT (Information and Communication Technologies) tools. To this aim, we consider as a case study the port of Trieste (Italy) and we model the system in a Petri net framework. The port logistics and the truck traffic are described in different operative conditions characterized by different levels of ICT integration and information sharing between infrastructures and operators. Moreover, the system is simulated in the Matlab environment under different traffic scenarios and system capacity assumptions. The simulation results show that ICT have a huge potential for efficient real time management and operation of LIS. © 2009 EUCA.},
  keywords = {MATLAB; Petri nets; Ports and harbors; ICT integrations; Information and Communication Technologies; Information sharing; Intermodal system; MATLAB environment; Petri net models; Real-time management; System Capacity; Information management},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M., Fanti, M. P., Iacobellis, G. & Rotunno, G. (2014) An integrated technique for the internal logistics analysis and management in discrete manufacturing systems. IN International Journal of Computer Integrated Manufacturing, 27.165 – 180. doi:10.1080/0951192X.2013.802370
  [BibTeX] [Abstract] [Download PDF]

  A novel hierarchical and iterative technique is presented for the analysis and management of the internal logistics of manufacturing systems. The method effectively integrates the value stream mapping (VSM) tool, the analytic hierarchy process (AHP) approach, and discrete event simulation. Starting from a concise description of the manufacturing system obtained by the VSM graphical approach, so as to identify nonvalue-adding activities, a detailed and standardised description is obtained by the unified modelling language (UML). Then the AHP technique is used to rank the system anomalies, singling out the major ones. Further application of the VSM tool produces an overall picture of the desired manufacturing system internal flow, and the UML description details the to-be system activities. Finally, the use of discrete event simulation allows the quantitative verification of the effects of the changes in the production system. The proposed technique is a tool to systematically improve the internal logistics of complex production systems while assessing the system dynamics and corresponding performance improvements. An application of the method to a real case study enlightens its effectiveness. © 2013 Taylor & Francis.

  @ARTICLE{Dotoli2014165,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio and Rotunno, Giuliana},
  title = {An integrated technique for the internal logistics analysis and management in discrete manufacturing systems},
  year = {2014},
  journal = {International Journal of Computer Integrated Manufacturing},
  volume = {27},
  number = {2},
  pages = {165 – 180},
  doi = {10.1080/0951192X.2013.802370},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84890121908&doi=10.1080%2f0951192X.2013.802370&partnerID=40&md5=c70041fa7c1c279e6da5613a202224e7},
  abstract = {A novel hierarchical and iterative technique is presented for the analysis and management of the internal logistics of manufacturing systems. The method effectively integrates the value stream mapping (VSM) tool, the analytic hierarchy process (AHP) approach, and discrete event simulation. Starting from a concise description of the manufacturing system obtained by the VSM graphical approach, so as to identify nonvalue-adding activities, a detailed and standardised description is obtained by the unified modelling language (UML). Then the AHP technique is used to rank the system anomalies, singling out the major ones. Further application of the VSM tool produces an overall picture of the desired manufacturing system internal flow, and the UML description details the to-be system activities. Finally, the use of discrete event simulation allows the quantitative verification of the effects of the changes in the production system. The proposed technique is a tool to systematically improve the internal logistics of complex production systems while assessing the system dynamics and corresponding performance improvements. An application of the method to a real case study enlightens its effectiveness. © 2013 Taylor & Francis.},
  author_keywords = {analytic hierarchy process; discrete event simulation; internal logistics; manufacturing systems; unified modelling language; value stream mapping},
  keywords = {Analytic hierarchy process; Computer hardware description languages; Computer simulation languages; Hierarchical systems; Iterative methods; Manufacture; Mapping; Modeling languages; Unified Modeling Language; Analytic hierarchy process (ahp); Complex production systems; Discrete manufacturing systems; Integrated techniques; Internal Logistics; Iterative technique; Quantitative verification; Value stream mapping; Discrete event simulation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 13}
  }

2013

• Dotoli, M., Epicoco, N., Falagario, M. & Costantino, N. (2013) A lean warehousing integrated approach: A case study IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA.. doi:10.1109/ETFA.2013.6648030
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on reengineering of production warehouses with lean manufacturing. Using as a case study an Italian interior design producer, we present an integrated approach for lean warehousing. Firstly a detailed description of the warehouse logistics is provided by the Unified Modeling Language (UML), hence Value Stream Mapping (VSM) allows identifying non-value adding activities, and the Gemba Shikumi technique helps to rank such anomalies. The reapplication of VSM produces an overall picture of the optimized warehouse, and using UML we detail the reengineered warehouse processes. The approach represents a useful tool to systematically improve production warehouse management. © 2013 IEEE.

  @CONFERENCE{Dotoli2013,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Costantino, Nicola},
  title = {A lean warehousing integrated approach: A case study},
  year = {2013},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  doi = {10.1109/ETFA.2013.6648030},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84890747024&doi=10.1109%2fETFA.2013.6648030&partnerID=40&md5=f13085b97bcc615f313821862675c0ce},
  abstract = {This paper focuses on reengineering of production warehouses with lean manufacturing. Using as a case study an Italian interior design producer, we present an integrated approach for lean warehousing. Firstly a detailed description of the warehouse logistics is provided by the Unified Modeling Language (UML), hence Value Stream Mapping (VSM) allows identifying non-value adding activities, and the Gemba Shikumi technique helps to rank such anomalies. The reapplication of VSM produces an overall picture of the optimized warehouse, and using UML we detail the reengineered warehouse processes. The approach represents a useful tool to systematically improve production warehouse management. © 2013 IEEE.},
  keywords = {Architectural design; Factory automation; Integrated control; Unified Modeling Language; Integrated approach; Interior designs; Lean manufacturing; Lean warehousing; Value stream mapping; Warehouse management; Warehouses},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Dotoli, M., Sciancalepore, F., Epicoco, N., Falagario, M., Turchiano, B. & Costantino, N. (2013) A periodic event scheduling approach for offline timetable optimization of regional railways IN 2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013., 849 – 854. doi:10.1109/ICNSC.2013.6548849
  [BibTeX] [Abstract] [Download PDF]

  We address the train timetabling problem for regional rails by a cyclic scheduling approach. We revisit a mixed integer linear programming model for offline timetable optimization and enhance it using a discrete event formulation and taking into account single-track stations that typically characterize local rails. The model can be applied to regional railways that are increasingly gaining significance due to the social pressure for sustainable mobility. The approach is successfully applied to a large portion of a real Southern Italy railway network, obtaining a timetable that enhances the passengers service level. © 2013 IEEE.

  @CONFERENCE{Dotoli2013849,
  author = {Dotoli, Mariagrazia and Sciancalepore, Fabio and Epicoco, Nicola and Falagario, Marco and Turchiano, Biagio and Costantino, Nicola},
  title = {A periodic event scheduling approach for offline timetable optimization of regional railways},
  year = {2013},
  journal = {2013 10th IEEE International Conference on Networking, Sensing and Control, ICNSC 2013},
  pages = {849 – 854},
  doi = {10.1109/ICNSC.2013.6548849},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84881269306&doi=10.1109%2fICNSC.2013.6548849&partnerID=40&md5=e184d97b5e9540259e36989575a8073c},
  abstract = {We address the train timetabling problem for regional rails by a cyclic scheduling approach. We revisit a mixed integer linear programming model for offline timetable optimization and enhance it using a discrete event formulation and taking into account single-track stations that typically characterize local rails. The model can be applied to regional railways that are increasingly gaining significance due to the social pressure for sustainable mobility. The approach is successfully applied to a large portion of a real Southern Italy railway network, obtaining a timetable that enhances the passengers service level. © 2013 IEEE.},
  author_keywords = {events; management; optimization; Railways; regional networks; scheduling algorithms; train timetable},
  keywords = {Discrete event simulation; Linear programming; Management; Optimization; Railroads; Scheduling; Scheduling algorithms; Cyclic scheduling; events; Mixed integer linear programming model; Railways; Regional networks; Sustainable mobility; Train timetables; Train timetabling problem; Railroad transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Costantino, N., Dotoli, M., Epicoco, N., Falagario, M. & Sciancalepore, F. (2013) Using cross-efficiency fuzzy Data Envelopment Analysis for healthcare facilities performance evaluation under uncertainty IN Proceedings – 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013., 912 – 917. doi:10.1109/SMC.2013.160
  [BibTeX] [Abstract] [Download PDF]

  address the problem of healthcare systems performance evaluation under uncertainty by a cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique. Triangular fuzzy numbers are employed to deal with uncertain data. More precisely, a fuzzy triangular efficiency is associated to each hospital/ward through a cross-evaluation by a compromise between objectives. Results are defuzzified to obtain the ranking. The method is applied to evaluate hospitals in a region of Southern Italy and estimate the temporal evolution of the performance of one of them, showing the ease of application and usefulness in validating and planning healthcare reforms. © 2013 IEEE.

  @CONFERENCE{Costantino2013912,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Sciancalepore, Fabio},
  title = {Using cross-efficiency fuzzy Data Envelopment Analysis for healthcare facilities performance evaluation under uncertainty},
  year = {2013},
  journal = {Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013},
  pages = {912 – 917},
  doi = {10.1109/SMC.2013.160},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893537583&doi=10.1109%2fSMC.2013.160&partnerID=40&md5=c8c238d8356ba6d8cbe50e98c573a3c4},
  abstract = {address the problem of healthcare systems performance evaluation under uncertainty by a cross-efficiency fuzzy Data Envelopment Analysis (DEA) technique. Triangular fuzzy numbers are employed to deal with uncertain data. More precisely, a fuzzy triangular efficiency is associated to each hospital/ward through a cross-evaluation by a compromise between objectives. Results are defuzzified to obtain the ranking. The method is applied to evaluate hospitals in a region of Southern Italy and estimate the temporal evolution of the performance of one of them, showing the ease of application and usefulness in validating and planning healthcare reforms. © 2013 IEEE.},
  keywords = {Cybernetics; Data envelopment analysis; Efficiency; Fuzzy sets; Cross-efficiency; Fuzzy data envelopment analysis; Health-care system; Healthcare facility; Healthcare reforms; Temporal evolution; Triangular fuzzy numbers; Uncertain datas; Health care},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Dotoli, M., Hammadi, S., Jeribi, K., Russo, C. & Zgaya, H. (2013) A multi-agent Decision Support System for optimization of co-modal transportation route planning services IN Proceedings of the IEEE Conference on Decision and Control., 911 – 916. doi:10.1109/CDC.2013.6759998
  [BibTeX] [Abstract] [Download PDF]

  We present a Decision Support System (DSS) for co-modal transportation. The DSS answers multiple route planning requests in a co-modal setting with vehicle preference and conflicting criteria, e.g., costs, time, and gas emissions minimization. The DSS architecture is based on the inherently distributed multi-agent systems framework that allows the decomposition of the route planning problem into multiple simpler tasks. A genetic algorithm is employed to obtain the optimal user-vehicle-route combinations according to the users preferences. The DSS is tested simulating itinerary requests with conflicting preferences in Nord Pas de Calais (France). © 2013 IEEE.

  @CONFERENCE{Dotoli2013911,
  author = {Dotoli, Mariagrazia and Hammadi, Slim and Jeribi, Karama and Russo, Carmine and Zgaya, Hayfa},
  title = {A multi-agent Decision Support System for optimization of co-modal transportation route planning services},
  year = {2013},
  journal = {Proceedings of the IEEE Conference on Decision and Control},
  pages = {911 – 916},
  doi = {10.1109/CDC.2013.6759998},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902324424&doi=10.1109%2fCDC.2013.6759998&partnerID=40&md5=e506e71d6e9b41c8f5512862f40db5ec},
  abstract = {We present a Decision Support System (DSS) for co-modal transportation. The DSS answers multiple route planning requests in a co-modal setting with vehicle preference and conflicting criteria, e.g., costs, time, and gas emissions minimization. The DSS architecture is based on the inherently distributed multi-agent systems framework that allows the decomposition of the route planning problem into multiple simpler tasks. A genetic algorithm is employed to obtain the optimal user-vehicle-route combinations according to the users preferences. The DSS is tested simulating itinerary requests with conflicting preferences in Nord Pas de Calais (France). © 2013 IEEE.},
  keywords = {Decision support systems; Gas emissions; Genetic algorithms; Transportation routes; Conflicting preferences; Decision support system (dss); Distributed multiagent systems; Multi agent; Multiple routes; Route planning; Multi agent systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 15}
  }

• Fanti, M. P., Mangini, A. M., Dotoli, M. & Ukovich, W. (2013) A three-level strategy for the design and performance evaluation of hospital departments. IN IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, 43.742 – 756. doi:10.1109/TSMCA.2012.2217319
  [BibTeX] [Abstract] [Download PDF]

  The efficient management of hospital departments (HDs) has recently become an important issue. Indeed, the increased demand and design for hospital services have saturated the capacity of HD that requires suitable tools for the efficient use of resources and flow of patients, staff, and drugs. This paper proposes a model based on a three-level strategy to design at the tactical level in a concise and effective way the structure, the resources, and the dynamics of a critically congested HD. The design strategy is composed of three basic elements: the modeling module, the optimization module, and the simulation and decision module. The first module employs a UnifiedModeling Language tool and a timed Petri net (PN) model to effectively capture the detailed flow and dynamics of patients, starting from their arrival to the HD until their discharge. The optimization module employs the fluid relaxation to concisely approximate in a continuous PN framework the HD model and optimize suitable performance indices. The simulation module verifies that the optimized parameters allow an effective workflow organization while maximizing the patient flow. In case of inconsistencies due to the fluid approximation between the continuous model used in the design phase by the optimization module and the discrete one used in the subsequent verification phase by the simulation module, the latter module revises the values of some HD model parameters. A real case study on the Emergency Cardiology Department of the General Hospital of Bari (Italy) shows the efficiency and accuracy of the proposed method. © 2013 IEEE.

  @ARTICLE{Fanti2013742,
  author = {Fanti, Maria Pia and Mangini, Agostino Marcello and Dotoli, Mariagrazia and Ukovich, Walter},
  title = {A three-level strategy for the design and performance evaluation of hospital departments},
  year = {2013},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans},
  volume = {43},
  number = {4},
  pages = {742 – 756},
  doi = {10.1109/TSMCA.2012.2217319},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887038165&doi=10.1109%2fTSMCA.2012.2217319&partnerID=40&md5=af8a84aa963d24f0c3b58a21a6606eef},
  abstract = {The efficient management of hospital departments (HDs) has recently become an important issue. Indeed, the increased demand and design for hospital services have saturated the capacity of HD that requires suitable tools for the efficient use of resources and flow of patients, staff, and drugs. This paper proposes a model based on a three-level strategy to design at the tactical level in a concise and effective way the structure, the resources, and the dynamics of a critically congested HD. The design strategy is composed of three basic elements: the modeling module, the optimization module, and the simulation and decision module. The first module employs a UnifiedModeling Language tool and a timed Petri net (PN) model to effectively capture the detailed flow and dynamics of patients, starting from their arrival to the HD until their discharge. The optimization module employs the fluid relaxation to concisely approximate in a continuous PN framework the HD model and optimize suitable performance indices. The simulation module verifies that the optimized parameters allow an effective workflow organization while maximizing the patient flow. In case of inconsistencies due to the fluid approximation between the continuous model used in the design phase by the optimization module and the discrete one used in the subsequent verification phase by the simulation module, the latter module revises the values of some HD model parameters. A real case study on the Emergency Cardiology Department of the General Hospital of Bari (Italy) shows the efficiency and accuracy of the proposed method. © 2013 IEEE.},
  author_keywords = {Healthcare systems; Modeling; Performance evaluation; Petri nets (PNs); Simulation},
  keywords = {Design; Hospitals; Models; Optimization; Petri nets; Tools; Hospitals; Models; Petri nets; Efficient managements; Health-care system; Optimization module; Optimized parameter; Performance evaluation; Performance indices; Petri nets (PNs); Simulation; Continuous modeling; Efficient managements; Fluid approximation; Health-care system; Optimization module; Performance evaluation; Petri nets (PNs); Simulation; Computer simulation; Unified Modeling Language},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 53}
  }

• Dotoli, M., Epicoco, N., Falagario, M., Palma, D. & Turchiano, B. (2013) A train load planning optimization model for intermodal freight transport terminals: A case study IN Proceedings – 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013., 3597 – 3602. doi:10.1109/SMC.2013.613
  [BibTeX] [Abstract] [Download PDF]

  Despite the emerging positive trend of rail freight transport, especially in intermodal contexts, the optimization of intermodal terminals is addressed only by few studies and mainly for seaport terminals. This paper fills this gap presenting a train load1 planning optimization model for intermodal rail-road terminals. The proposed model maximizes the train commercial value while respecting priority, physical, financial, and prosecution constraints (i.e., taking into account containers that prosecute to a subsequent terminal after the train destination). The presented method has been successfully tested on a real case study – The rail-road terminal of an Italian intermodal logistics company that is a leader in the European market – showing its effectiveness and ease of application. © 2013 IEEE.

  @CONFERENCE{Dotoli20133597,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Palma, Domenico and Turchiano, Biagio},
  title = {A train load planning optimization model for intermodal freight transport terminals: A case study},
  year = {2013},
  journal = {Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013},
  pages = {3597 – 3602},
  doi = {10.1109/SMC.2013.613},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893630792&doi=10.1109%2fSMC.2013.613&partnerID=40&md5=6f33f8006bb4631e581bf192e55b9724},
  abstract = {Despite the emerging positive trend of rail freight transport, especially in intermodal contexts, the optimization of intermodal terminals is addressed only by few studies and mainly for seaport terminals. This paper fills this gap presenting a train load1 planning optimization model for intermodal rail-road terminals. The proposed model maximizes the train commercial value while respecting priority, physical, financial, and prosecution constraints (i.e., taking into account containers that prosecute to a subsequent terminal after the train destination). The presented method has been successfully tested on a real case study - The rail-road terminal of an Italian intermodal logistics company that is a leader in the European market - showing its effectiveness and ease of application. © 2013 IEEE.},
  keywords = {Cybernetics; Mathematical models; Roads and streets; European markets; Intermodal freight transport; Intermodal terminals; Logistics company; Optimization modeling; Rail freights; Rail-road terminals; Real case; Freight transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P., Mangini, A. M., Sciancalepore, F. & Ukovich, W. (2013) A hierarchical optimization technique for the strategic design of distribution networks. IN Computers and Industrial Engineering, 66.849 – 864. doi:10.1016/j.cie.2013.09.009
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the optimal design of the last supply chain branch, i.e., the Distribution Network (DN), starting from manufacturers till the retailers. It considers a distributed system composed of different stages connected by material links labeled with suitable performance indices. A hierarchical procedure employing direct graph (digraph) modeling, mixed integer linear programming, and the Analytic Hierarchy Process (AHP) is presented to select the optimal DN configuration. More in detail, a first-level DN optimization problem taking into account the definition and evaluation of the distribution chain performance provides a set of Pareto optimal solutions defined by digraph modeling. A second level DN optimization using the AHP method selects, on the basis of further criteria, the DN configuration from the Pareto face alternatives. To show the method effectiveness, the optimization model is applied to a case study describing an Italian regional healthcare drug DN. The problem solution by the proposed design method allows improving the DN flexibility and performance. © 2013 Elsevier Ltd. All rights reserved.

  @ARTICLE{Costantino2013849,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Fanti, Maria Pia and Mangini, Agostino Marcello and Sciancalepore, Fabio and Ukovich, Walter},
  title = {A hierarchical optimization technique for the strategic design of distribution networks},
  year = {2013},
  journal = {Computers and Industrial Engineering},
  volume = {66},
  number = {4},
  pages = {849 – 864},
  doi = {10.1016/j.cie.2013.09.009},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84888288538&doi=10.1016%2fj.cie.2013.09.009&partnerID=40&md5=187777eb599e31cf44e2b5af060c6ecd},
  abstract = {The paper addresses the optimal design of the last supply chain branch, i.e., the Distribution Network (DN), starting from manufacturers till the retailers. It considers a distributed system composed of different stages connected by material links labeled with suitable performance indices. A hierarchical procedure employing direct graph (digraph) modeling, mixed integer linear programming, and the Analytic Hierarchy Process (AHP) is presented to select the optimal DN configuration. More in detail, a first-level DN optimization problem taking into account the definition and evaluation of the distribution chain performance provides a set of Pareto optimal solutions defined by digraph modeling. A second level DN optimization using the AHP method selects, on the basis of further criteria, the DN configuration from the Pareto face alternatives. To show the method effectiveness, the optimization model is applied to a case study describing an Italian regional healthcare drug DN. The problem solution by the proposed design method allows improving the DN flexibility and performance. © 2013 Elsevier Ltd. All rights reserved.},
  author_keywords = {Analytic hierarchy process; Digraph modeling; Distribution network; Mixed integer linear programming; Optimization; Supply chain},
  keywords = {Analytic hierarchy process; Directed graphs; Electric power distribution; Hierarchical systems; Linear programming; Optimal systems; Supply chains; Analytic hierarchy process (ahp); Digraph models; Hierarchical optimization; Mixed integer linear programming; Optimization modeling; Optimization problems; Pareto optimal solutions; Performance indices; Optimization},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 15}
  }

• Dassisti, M., Dotoli, M. & Chen, D. (2013) Interoperability analysis: General concepts for an axiomatic approach IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA.. doi:10.1109/ETFA.2013.6648169
  [BibTeX] [Abstract] [Download PDF]

  The paper provides general criteria and evidences for the design phase of an interoperable enterprise system. The analysis of interoperability is introduced, to characterize features and criticalities for the subsequent design actions to be undertaken. An axiomatic approach is proposed to this aim, providing general principles to be followed. A simple case study is discussed. © 2013 IEEE.

  @CONFERENCE{Dassisti2013,
  author = {Dassisti, Michele and Dotoli, Mariagrazia and Chen, David},
  title = {Interoperability analysis: General concepts for an axiomatic approach},
  year = {2013},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  doi = {10.1109/ETFA.2013.6648169},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84890751533&doi=10.1109%2fETFA.2013.6648169&partnerID=40&md5=d78c6370027430a4085515afb0068181},
  abstract = {The paper provides general criteria and evidences for the design phase of an interoperable enterprise system. The analysis of interoperability is introduced, to characterize features and criticalities for the subsequent design actions to be undertaken. An axiomatic approach is proposed to this aim, providing general principles to be followed. A simple case study is discussed. © 2013 IEEE.},
  keywords = {Factory automation; Axiomatic approach; Design phase; Enterprise system; Interoperability},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M., Epicoco, N., Falagario, M., Piconese, A., Sciancalepore, F. & Turchiano, B. (2013) A real time traffic management model for regional railway networks under disturbances IN IEEE International Conference on Automation Science and Engineering., 892 – 897. doi:10.1109/CoASE.2013.6653977
  [BibTeX] [Abstract] [Download PDF]

  We address real time traffic management under disturbances of regional rails with a centralized traffic control system. We solve the rescheduling problem by revisiting a finite time horizon mixed integer linear programming model from the related literature. First, we adapt the framework to regional networks, in which stations are close and the network is mainly constituted by single tracks; second, to solve train conflicts that may occur in the rescheduled timetable after the chosen time horizon, we enhance the model by an iterative heuristic algorithm that solves such conflicts. The presented approach is applied to a real data set related to a large portion of a regional network in Southern Italy, showing its effectiveness in providing a physically realizable rescheduled solution in a very short computational time. © 2013 IEEE.

  @CONFERENCE{Dotoli2013892,
  author = {Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Piconese, Astrid and Sciancalepore, Fabio and Turchiano, Biagio},
  title = {A real time traffic management model for regional railway networks under disturbances},
  year = {2013},
  journal = {IEEE International Conference on Automation Science and Engineering},
  pages = {892 – 897},
  doi = {10.1109/CoASE.2013.6653977},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891508996&doi=10.1109%2fCoASE.2013.6653977&partnerID=40&md5=10f312c662a1b1efe1bca6fbc2462d33},
  abstract = {We address real time traffic management under disturbances of regional rails with a centralized traffic control system. We solve the rescheduling problem by revisiting a finite time horizon mixed integer linear programming model from the related literature. First, we adapt the framework to regional networks, in which stations are close and the network is mainly constituted by single tracks; second, to solve train conflicts that may occur in the rescheduled timetable after the chosen time horizon, we enhance the model by an iterative heuristic algorithm that solves such conflicts. The presented approach is applied to a real data set related to a large portion of a regional network in Southern Italy, showing its effectiveness in providing a physically realizable rescheduled solution in a very short computational time. © 2013 IEEE.},
  author_keywords = {events; optimization; Railways; real time conflict resolution; regional networks; train scheduling; train timetable},
  keywords = {Embedded systems; Heuristic algorithms; Iterative methods; Linear programming; Optimization; Railroads; events; Railways; Real time conflict resolution; Regional networks; Train scheduling; Train timetables; Scheduling},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Carli, R., Dotoli, M., Pellegrino, R. & Ranieri, L. (2013) Measuring and managing the smartness of cities: A framework for classifying performance indicators IN Proceedings – 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013., 1288 – 1293. doi:10.1109/SMC.2013.223
  [BibTeX] [Abstract] [Download PDF]

  Due to the continuous increase of the world population living in cities, it is crucial to identify strategic plans and perform associated actions to make cities smarter, i.e., more operationally efficient, socially friendly, and environmentally sustainable, in a cost effective manner. To achieve these goals, emerging smart cities need to be optimally and intelligently measured, monitored, and managed. In this context the paper proposes the development of a framework for classifying performance indicators of a smart city. It is based on two dimensions: The degree of objectivity of observed variables and the level of technological advancement for data collection. The paper shows an application of the presented framework to the case of the Bari municipality (Italy). © 2013 IEEE.

  @CONFERENCE{Carli20131288,
  author = {Carli, Raffaele and Dotoli, Mariagrazia and Pellegrino, Roberta and Ranieri, Luigi},
  title = {Measuring and managing the smartness of cities: A framework for classifying performance indicators},
  year = {2013},
  journal = {Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013},
  pages = {1288 – 1293},
  doi = {10.1109/SMC.2013.223},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893629343&doi=10.1109%2fSMC.2013.223&partnerID=40&md5=2e7a1d0751ad2b7391780dc51c8b26b0},
  abstract = {Due to the continuous increase of the world population living in cities, it is crucial to identify strategic plans and perform associated actions to make cities smarter, i.e., more operationally efficient, socially friendly, and environmentally sustainable, in a cost effective manner. To achieve these goals, emerging smart cities need to be optimally and intelligently measured, monitored, and managed. In this context the paper proposes the development of a framework for classifying performance indicators of a smart city. It is based on two dimensions: The degree of objectivity of observed variables and the level of technological advancement for data collection. The paper shows an application of the presented framework to the case of the Bari municipality (Italy). © 2013 IEEE.},
  author_keywords = {Information and communication technologies; Management; Monitoring; Smart cities; Smartness indicators},
  keywords = {Cybernetics; Electronic commerce; Information technology; Management; Monitoring; Cost effective; Data collection; Information and Communication Technologies; Performance indicators; Smart cities; Strategic plan; Technological advancement; World population; Benchmarking},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 91}
  }

2012

• Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P. & Mangini, A. M. (2012) A model for supply management of agile manufacturing supply chains. IN International Journal of Production Economics, 135.451 – 457. doi:10.1016/j.ijpe.2011.08.021
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses the configuration problem of Manufacturing Supply Chains (MSC) with reference to the supply planning issue. Assuming that the manufacturing system is composed of different stages, we present a technique for the strategic management of the chain addressing supply planning and allowing the improvement of the MSC agility in terms of ability in reconfiguration to meet performance. More in detail, we enhance a previous design method by some of the authors that employs digraph modeling and integer linear programming to optimally design the MSC. The original approach avoids supply chain disruption and stock out and, at the same time, can manage spare parts distribution. In order to take into account the level of demands and maximum production capacities with single/multiple sourcing, in this new formulation we introduce supplier capacity constraints. A case study is presented describing the optimal MSC configuration of an Italian manufacturing firm. The obtained results show that the design method provides managers with key answers to issues related to the supply chain strategic configuration and agility, e.g., choosing the right location for distributors and retailers for enhanced MSC flexibility and performance. © 2010 Elsevier B.V. All rights reserved.

  @ARTICLE{Costantino2012451,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Fanti, Maria Pia and Mangini, Agostino Marcello},
  title = {A model for supply management of agile manufacturing supply chains},
  year = {2012},
  journal = {International Journal of Production Economics},
  volume = {135},
  number = {1},
  pages = {451 – 457},
  doi = {10.1016/j.ijpe.2011.08.021},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80055047016&doi=10.1016%2fj.ijpe.2011.08.021&partnerID=40&md5=f210a506728cdb2f214b3087f73c28a0},
  abstract = {This paper addresses the configuration problem of Manufacturing Supply Chains (MSC) with reference to the supply planning issue. Assuming that the manufacturing system is composed of different stages, we present a technique for the strategic management of the chain addressing supply planning and allowing the improvement of the MSC agility in terms of ability in reconfiguration to meet performance. More in detail, we enhance a previous design method by some of the authors that employs digraph modeling and integer linear programming to optimally design the MSC. The original approach avoids supply chain disruption and stock out and, at the same time, can manage spare parts distribution. In order to take into account the level of demands and maximum production capacities with single/multiple sourcing, in this new formulation we introduce supplier capacity constraints. A case study is presented describing the optimal MSC configuration of an Italian manufacturing firm. The obtained results show that the design method provides managers with key answers to issues related to the supply chain strategic configuration and agility, e.g., choosing the right location for distributors and retailers for enhanced MSC flexibility and performance. © 2010 Elsevier B.V. All rights reserved.},
  author_keywords = {Agile manufacturing; Integer linear programming; Performance optimization; Sourcing strategy; Strategic design; Supply chain; Supply planning},
  keywords = {Design; Integer programming; Linear programming; Manufacture; Optimization; Planning; Supply chains; Agile manufacturing; Integer Linear Programming; Performance optimizations; Sourcing strategies; Strategic design; Supply planning; Supply chain management},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 113}
  }

• Dotoli, M., Fanti, M. P., Iacobellis, G. & Rotunno, G. (2012) A lean manufacturing strategy using Value Stream Mapping, the Unified Modeling Language, and discrete event simulation IN IEEE International Conference on Automation Science and Engineering., 668 – 673. doi:10.1109/CoASE.2012.6386328
  [BibTeX] [Abstract] [Download PDF]

  The paper presents a lean manufacturing strategy integrating Value Stream Mapping (VSM), the Unified Modeling Language (UML), and discrete event simulation. The procedure is iterative and hierarchical. Starting from a detailed description of the manufacturing process by the Unified Modeling Language (UML), the VSM graphical approach allows the identification and removal of non-value adding activities. The re-designed manufacturing system is represented in detail by UML to describe the novel system activities. The use of discrete event simulation allows the verification of the updated production system. Applying the lean manufacturing strategy to a real case study shows its effectiveness. © 2012 IEEE.

  @CONFERENCE{Dotoli2012668,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio and Rotunno, Giuliana},
  title = {A lean manufacturing strategy using Value Stream Mapping, the Unified Modeling Language, and discrete event simulation},
  year = {2012},
  journal = {IEEE International Conference on Automation Science and Engineering},
  pages = {668 – 673},
  doi = {10.1109/CoASE.2012.6386328},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872560932&doi=10.1109%2fCoASE.2012.6386328&partnerID=40&md5=e264657a36d4ce9dffa794bb01d51baa},
  abstract = {The paper presents a lean manufacturing strategy integrating Value Stream Mapping (VSM), the Unified Modeling Language (UML), and discrete event simulation. The procedure is iterative and hierarchical. Starting from a detailed description of the manufacturing process by the Unified Modeling Language (UML), the VSM graphical approach allows the identification and removal of non-value adding activities. The re-designed manufacturing system is represented in detail by UML to describe the novel system activities. The use of discrete event simulation allows the verification of the updated production system. Applying the lean manufacturing strategy to a real case study shows its effectiveness. © 2012 IEEE.},
  keywords = {Agile manufacturing systems; Discrete event simulation; Production engineering; Sustainable development; Graphical approach; Identification and removal; Lean manufacturing; Manufacturing process; Production system; Value stream mapping; Unified Modeling Language},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 12}
  }

• Costantino, N., Dotoli, M., Epicoco, N., Falagario, M. & Sciancalepore, F. (2012) A novel fuzzy Data Envelopment Analysis methodology for performance evaluation in a two-stage supply chain IN IEEE International Conference on Automation Science and Engineering., 974 – 979. doi:10.1109/CoASE.2012.6386424
  [BibTeX] [Abstract] [Download PDF]

  The paper presents a novel fuzzy Data Envelopment Analysis (DEA) technique for supplier selection under uncertainty. Uncertain input and output data characterizing suppliers are estimated through triangular fuzzy numbers. The resulting fuzzy triangular efficiency is determined by using only a set of weights, derived as a compromise between objectives. The obtained results are defuzzified and compared in order to rank suppliers. The presented method is applied for the evaluation of a set of candidate suppliers of an SME located in Southern Italy, showing the ease of application and the discriminative power between different suppliers under uncertain data. © 2012 IEEE.

  @CONFERENCE{Costantino2012974,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Sciancalepore, Fabio},
  title = {A novel fuzzy Data Envelopment Analysis methodology for performance evaluation in a two-stage supply chain},
  year = {2012},
  journal = {IEEE International Conference on Automation Science and Engineering},
  pages = {974 – 979},
  doi = {10.1109/CoASE.2012.6386424},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872577763&doi=10.1109%2fCoASE.2012.6386424&partnerID=40&md5=b2827d406d9283b494377059cae5d3fe},
  abstract = {The paper presents a novel fuzzy Data Envelopment Analysis (DEA) technique for supplier selection under uncertainty. Uncertain input and output data characterizing suppliers are estimated through triangular fuzzy numbers. The resulting fuzzy triangular efficiency is determined by using only a set of weights, derived as a compromise between objectives. The obtained results are defuzzified and compared in order to rank suppliers. The presented method is applied for the evaluation of a set of candidate suppliers of an SME located in Southern Italy, showing the ease of application and the discriminative power between different suppliers under uncertain data. © 2012 IEEE.},
  keywords = {Fuzzy sets; Supply chains; Sustainable development; Fuzzy data envelopment analysis; Input and outputs; Performance evaluation; Southern Italy; Supplier selection; Triangular fuzzy numbers; Uncertain datas; Data envelopment analysis},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Costantino, N., Dotoli, M., Epicoco, N., Falagario, M. & Sciancalepore, F. (2012) A cross efficiency fuzzy data envelopment analysis technique for supplier evaluation under uncertainty IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA.. doi:10.1109/ETFA.2012.6489600
  [BibTeX] [Abstract] [Download PDF]

  We present a novel cross efficiency fuzzy Data Envelopment Analysis (DEA) technique for supplier selection under uncertainty. In order to deal with uncertain input and output suppliers data, triangular fuzzy numbers are employed. A fuzzy triangular efficiency is associated to each supplier through a cross evaluation by a compromise between objectives. The results are defuzzified and a supplier ranking is determined. The method is applied to the evaluation of a set of candidate suppliers of an Italian SME, showing the ease of application and discriminative power among suppliers. © 2012 IEEE.

  @CONFERENCE{Costantino2012,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco and Sciancalepore, Fabio},
  title = {A cross efficiency fuzzy data envelopment analysis technique for supplier evaluation under uncertainty},
  year = {2012},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  doi = {10.1109/ETFA.2012.6489600},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876391183&doi=10.1109%2fETFA.2012.6489600&partnerID=40&md5=b3dd1395d6852890b4f3d746d87b1632},
  abstract = {We present a novel cross efficiency fuzzy Data Envelopment Analysis (DEA) technique for supplier selection under uncertainty. In order to deal with uncertain input and output suppliers data, triangular fuzzy numbers are employed. A fuzzy triangular efficiency is associated to each supplier through a cross evaluation by a compromise between objectives. The results are defuzzified and a supplier ranking is determined. The method is applied to the evaluation of a set of candidate suppliers of an Italian SME, showing the ease of application and discriminative power among suppliers. © 2012 IEEE.},
  keywords = {Data envelopment analysis; Factory automation; Fuzzy sets; Cross efficiency; Cross evaluation; Discriminative power; Fuzzy data envelopment analysis; Input and outputs; Supplier Evaluations; Supplier selection; Triangular fuzzy numbers; Efficiency},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 7}
  }

• Dassisti, M., Dotoli, M., Epicoco, N. & Falagario, M. (2012) Internal logistics integration by automated storage and retrieval systems: A reengineering case study. IN Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7567 LNCS.78 – 82. doi:10.1007/978-3-642-33618-8_14
  [BibTeX] [Abstract] [Download PDF]

  Nowadays, factors like globalization, productivity, and reduction of time-to-market make the impact of logistics on production by far wider than in the past. Such a complex scenario originated considerable interest for the design, planning and control of warehousing systems as new research topics (De Koster et al. 2007). However, in spite of the importance of warehouse design and management, authors agree on the lack of systematic approaches (Baker and Canessa, 2009). Moreover, the existing contributions do not typically consider the problem of warehouse design in a continuous improvement context. On the contrary, with the enhanced customer demand, for most manufacturing industries it has become increasingly important to continuously monitor and progress the internal logistics. This paper presents a preliminary study for the reengineering of the logistics in a Southern Italy firm producing shoes and accessories based on formal modeling. We address a widely used solution for warehouse material handling, i.e., Automated Storage and Retrieval Systems (AS/RSs) (Dotoli and Fanti 2007). These systems are a combination of automatic material handling and storage/retrieval equipments characterized by high accuracy and speed. In order to reengineer the logistic system, a Unified Modelling Language (UML) (Miles and Hamilton, 2006) model is adopted (Dassisti, 2003). © 2012 Springer-Verlag.

  @ARTICLE{Dassisti201278,
  author = {Dassisti, Michele and Dotoli, Mariagrazia and Epicoco, Nicola and Falagario, Marco},
  title = {Internal logistics integration by automated storage and retrieval systems: A reengineering case study},
  year = {2012},
  journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
  volume = {7567 LNCS},
  pages = {78 – 82},
  doi = {10.1007/978-3-642-33618-8_14},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873872454&doi=10.1007%2f978-3-642-33618-8_14&partnerID=40&md5=3274b476c3d73d1c0f5c5b77a0a548b7},
  abstract = {Nowadays, factors like globalization, productivity, and reduction of time-to-market make the impact of logistics on production by far wider than in the past. Such a complex scenario originated considerable interest for the design, planning and control of warehousing systems as new research topics (De Koster et al. 2007). However, in spite of the importance of warehouse design and management, authors agree on the lack of systematic approaches (Baker and Canessa, 2009). Moreover, the existing contributions do not typically consider the problem of warehouse design in a continuous improvement context. On the contrary, with the enhanced customer demand, for most manufacturing industries it has become increasingly important to continuously monitor and progress the internal logistics. This paper presents a preliminary study for the reengineering of the logistics in a Southern Italy firm producing shoes and accessories based on formal modeling. We address a widely used solution for warehouse material handling, i.e., Automated Storage and Retrieval Systems (AS/RSs) (Dotoli and Fanti 2007). These systems are a combination of automatic material handling and storage/retrieval equipments characterized by high accuracy and speed. In order to reengineer the logistic system, a Unified Modelling Language (UML) (Miles and Hamilton, 2006) model is adopted (Dassisti, 2003). © 2012 Springer-Verlag.},
  keywords = {Computer control systems; Design; Industry; Information retrieval; Internet; Materials handling; Reengineering; Research; Shoe manufacture; Unified Modeling Language; Warehouses; Automated storage and retrieval system; Continuous improvements; Customer demands; Formal modeling; Hamiltons; Logistics integration; Manufacturing industries; Material handling; Planning and control; Research topics; Southern Italy; Storage/retrieval; Time-to-market; Warehouse design; Warehousing systems; Logistics},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Bevilacqua, V., Dotoli, M., Foglia, M. M., Acciani, F., Tattoli, G. & Valori, M. (2012) Using artificial neural networks for closed loop control of a hydraulic prosthesis for a human elbow. IN Communications in Computer and Information Science, 304 CCIS.475 – 480. doi:10.1007/978-3-642-31837-5_69
  [BibTeX] [Abstract] [Download PDF]

  We address control of a hydraulic prosthesis for human elbow, a problem in which it is essential to obtain quick simulation results to appreciate the system dynamic. The forward kinematics problem for a prosthesis developed at Politecnico di Bari is solved using artificial neural networks as an effective and simple method to solve the problem in real time and limit computations. We show the method effectiveness designing two PID regulators that control the arm thanks to the neural computation of the forward kinematics. © 2012 Springer-Verlag.

  @ARTICLE{Bevilacqua2012475,
  author = {Bevilacqua, Vitoantonio and Dotoli, Mariagrazia and Foglia, Mario Massimo and Acciani, Francesco and Tattoli, Giacomo and Valori, Marcello},
  title = {Using artificial neural networks for closed loop control of a hydraulic prosthesis for a human elbow},
  year = {2012},
  journal = {Communications in Computer and Information Science},
  volume = {304 CCIS},
  pages = {475 – 480},
  doi = {10.1007/978-3-642-31837-5_69},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865034262&doi=10.1007%2f978-3-642-31837-5_69&partnerID=40&md5=e09af309dbd3fa7d0b330e6acb189f23},
  abstract = {We address control of a hydraulic prosthesis for human elbow, a problem in which it is essential to obtain quick simulation results to appreciate the system dynamic. The forward kinematics problem for a prosthesis developed at Politecnico di Bari is solved using artificial neural networks as an effective and simple method to solve the problem in real time and limit computations. We show the method effectiveness designing two PID regulators that control the arm thanks to the neural computation of the forward kinematics. © 2012 Springer-Verlag.},
  keywords = {Intelligent computing; Neural networks; Prosthetics; Closed-loop control; Forward kinematics; Forward kinematics problem; Neural computations; PID regulators; Real time; SIMPLE method; System Dynamics; Problem solving},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M. & Falagario, M. (2012) A hierarchical model for optimal supplier selection in multiple sourcing contexts. IN International Journal of Production Research, 50.2953 – 2967. doi:10.1080/00207543.2011.578167
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses a crucial objective of the strategic purchasing function in supply chains, i.e. optimal supplier selection. We present a hierarchical extension of the data envelopment analysis (DEA), the most widespread method for supplier rating in the literature, for application in a multiple sourcing strategy context. The proposed hierarchical technique is based on three levels. First, a modified DEA approach is used to evaluate the efficiency of each supplier according to some criteria proposed by the buyer. Second, the well known technique for order preference by similarities to ideal solution (TOPSIS) is applied to rank the maximally efficient suppliers given by the previous step. Third and finally, a linear programming problem is stated and solved to find the quantities to order from each maximally efficient supplier in the multiple sourcing context. The presented approach is able to straightforwardly discern between efficient and inefficient partners, avoid the confusion between efficient and effective suppliers and split the supply in a multiple sourcing context. The hierarchical model is applied to the supply of a C class component to show its robustness and effectiveness, while comparing it with the DEA and TOPSIS approaches. © 2012 Copyright Taylor and Francis Group, LLC.

  @ARTICLE{Dotoli20122953,
  author = {Dotoli, M. and Falagario, M.},
  title = {A hierarchical model for optimal supplier selection in multiple sourcing contexts},
  year = {2012},
  journal = {International Journal of Production Research},
  volume = {50},
  number = {11},
  pages = {2953 – 2967},
  doi = {10.1080/00207543.2011.578167},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84862706058&doi=10.1080%2f00207543.2011.578167&partnerID=40&md5=95c1c1570c66b58f6c2854505ff406f1},
  abstract = {This paper addresses a crucial objective of the strategic purchasing function in supply chains, i.e. optimal supplier selection. We present a hierarchical extension of the data envelopment analysis (DEA), the most widespread method for supplier rating in the literature, for application in a multiple sourcing strategy context. The proposed hierarchical technique is based on three levels. First, a modified DEA approach is used to evaluate the efficiency of each supplier according to some criteria proposed by the buyer. Second, the well known technique for order preference by similarities to ideal solution (TOPSIS) is applied to rank the maximally efficient suppliers given by the previous step. Third and finally, a linear programming problem is stated and solved to find the quantities to order from each maximally efficient supplier in the multiple sourcing context. The presented approach is able to straightforwardly discern between efficient and inefficient partners, avoid the confusion between efficient and effective suppliers and split the supply in a multiple sourcing context. The hierarchical model is applied to the supply of a C class component to show its robustness and effectiveness, while comparing it with the DEA and TOPSIS approaches. © 2012 Copyright Taylor and Francis Group, LLC.},
  author_keywords = {data envelopment analysis; linear programming; optimal supplier selection; supplier efficiency; supplier evaluation; supply chain; technique for order preference by similarities to ideal solution},
  keywords = {Data envelopment analysis; Hierarchical systems; Linear programming; Supply chains; Hierarchical model; Hierarchical techniques; Ideal solutions; Linear programming problem; Sourcing strategies; Supplier Evaluations; Supplier selection; Optimization},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 48; All Open Access, Green Open Access}
  }

• Costantino, N., Dotoli, M., Falagario, M. & Sciancalepore, F. (2012) Fuzzy network design of sustainable supply chains IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 1284 – 1289. doi:10.3182/20120523-3-RO-2023.00154
  [BibTeX] [Abstract] [Download PDF]

  The paper focuses on supply chain network design under uncertain conditions. In order to achieve a sustainable supply chain configuration, suitable indices such as CO2 emissions and energy consumption are considered. Uncertainty in such performance is addressed by a fuzzy possibility theory approach. In particular, this paper presents a technique employing fuzzy integer linear programming to design the optimally efficient and sustainable supply chain network. Closed loop solutions with reverse logistics are compared with traditional forward supply chain structures in order to obtain improved sustainability performance. A case study inspired from the related literature is presented to show the technique effectiveness. © 2012 IFAC.

  @CONFERENCE{Costantino20121284,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Sciancalepore, Fabio},
  title = {Fuzzy network design of sustainable supply chains},
  year = {2012},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {14},
  number = {PART 1},
  pages = {1284 – 1289},
  doi = {10.3182/20120523-3-RO-2023.00154},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866110328&doi=10.3182%2f20120523-3-RO-2023.00154&partnerID=40&md5=3acc286409d444bed5636977aac0cdef},
  abstract = {The paper focuses on supply chain network design under uncertain conditions. In order to achieve a sustainable supply chain configuration, suitable indices such as CO2 emissions and energy consumption are considered. Uncertainty in such performance is addressed by a fuzzy possibility theory approach. In particular, this paper presents a technique employing fuzzy integer linear programming to design the optimally efficient and sustainable supply chain network. Closed loop solutions with reverse logistics are compared with traditional forward supply chain structures in order to obtain improved sustainability performance. A case study inspired from the related literature is presented to show the technique effectiveness. © 2012 IFAC.},
  author_keywords = {Fuzzy integer linear programming; Network design; Supply chain; Sustainability},
  keywords = {Ecodesign; Energy utilization; Integer programming; Manufacture; Supply chains; Sustainable development; Closed-loop solution; Fuzzy integer linear programming; Network design; Supply chain network design; Supply chain structures; Sustainability performance; Sustainable supply chains; Uncertain condition; Fuzzy neural networks},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6; All Open Access, Bronze Open Access}
  }

• Cabasino, M. P., Dotoli, M. & Seatzu, C. (2012) Marking estimation of fuzzy Petri nets IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA.. doi:10.1109/ETFA.2012.6489737
  [BibTeX] [Abstract] [Download PDF]

  In this paper we deal with the problem of designing an observer for Petri nets under the assumption that all transitions may be observed but there exist some uncertainties in the initial marking. In particular, the information on the initial marking is given in terms of fuzzy markings by associating a discrete membership function with each place. Some ideas on how to extend the proposed approach to the case of unobservable transitions are also discussed. © 2012 IEEE.

  @CONFERENCE{Cabasino2012,
  author = {Cabasino, Maria Paola and Dotoli, Mariagrazia and Seatzu, Carla},
  title = {Marking estimation of fuzzy Petri nets},
  year = {2012},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  doi = {10.1109/ETFA.2012.6489737},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876358726&doi=10.1109%2fETFA.2012.6489737&partnerID=40&md5=8dfebfd27061e28bf211aaa621c20559},
  abstract = {In this paper we deal with the problem of designing an observer for Petri nets under the assumption that all transitions may be observed but there exist some uncertainties in the initial marking. In particular, the information on the initial marking is given in terms of fuzzy markings by associating a discrete membership function with each place. Some ideas on how to extend the proposed approach to the case of unobservable transitions are also discussed. © 2012 IEEE.},
  keywords = {Factory automation; Fuzzy Petri nets; Initial marking; Marking estimation; Unobservable; Petri nets},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M. (2012) Freeway traffic control via route guidance: An approach based on a First Order Hybrid Petri Nets model IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 350 – 355. doi:10.3182/20120606-3-NL-3011.00065
  [BibTeX] [Abstract] [Download PDF]

  The paper proposes an approach for real time control of freeways by route guidance, an emerging technique for efficient freeway management. A first order fluid approximation is employed to model in a modular framework the vehicle flows by first order hybrid Petri nets. The hybrid Petri nets formalism enables the network designer to choose suitable splitting rates to off-ramps to minimize congestion. The increased freeway operation is performed based on the state knowledge of the obtained linear discrete-time, time-varying state variable model of the freeway to react to unpredictable events such as the blocking of a lane due to an accident or to work in progress. The proposed route guidance approach is applied to a case study to show its effectiveness. © 2012 IFAC.

  @CONFERENCE{Dotoli2012350,
  author = {Dotoli, Mariagrazia},
  title = {Freeway traffic control via route guidance: An approach based on a First Order Hybrid Petri Nets model},
  year = {2012},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {45},
  number = {9},
  pages = {350 – 355},
  doi = {10.3182/20120606-3-NL-3011.00065},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866054742&doi=10.3182%2f20120606-3-NL-3011.00065&partnerID=40&md5=6646e62367508b087dd4c42831edaa42},
  abstract = {The paper proposes an approach for real time control of freeways by route guidance, an emerging technique for efficient freeway management. A first order fluid approximation is employed to model in a modular framework the vehicle flows by first order hybrid Petri nets. The hybrid Petri nets formalism enables the network designer to choose suitable splitting rates to off-ramps to minimize congestion. The increased freeway operation is performed based on the state knowledge of the obtained linear discrete-time, time-varying state variable model of the freeway to react to unpredictable events such as the blocking of a lane due to an accident or to work in progress. The proposed route guidance approach is applied to a case study to show its effectiveness. © 2012 IFAC.},
  author_keywords = {Modeling; Performance evaluation; Petri nets; Road traffic; Simulation; Traffic control},
  keywords = {Air navigation; Bottling plants; Hybrid systems; Models; Petri nets; Real time control; Traffic control; First-order hybrid Petri nets; Fluid approximation; Freeway operations; Freeway traffic controls; Performance evaluations; Road traffic; Simulation; State-variable model; Highway planning},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Bevilacqua, V., Costantino, N., Dotoli, M., Falagario, M. & Sciancalepore, F. (2012) Strategic design and multi-objective optimisation of distribution networks based on genetic algorithms. IN International Journal of Computer Integrated Manufacturing, 25.1139 – 1150. doi:10.1080/0951192X.2012.684719
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the optimal design of distribution networks (DNs). Considering a distributed system composed of stages connected by material links labelled with suitable performance indices, a procedure employing multiobjective genetic algorithms (MOGAs) is presented to select the optimal DN configuration. The paper enhances a deterministic procedure for DN strategic configuration by employing MOGACOP, a real-valued chromosome MOGA that can be applied to the case of constrained nonlinear function. The main MOGA characteristics are the presence of three populations: two reference sets of individuals satisfying all constraints, namely, a set of Pareto optimal individuals (frontier population) and a set of individuals covering the previous population (archive population), together with a search set which, on the contrary, includes individuals that are allowed to not satisfy all constraints (laboratory population). MOGACOP allows solving the DN design nonlinear problem, which exhibits a multi-objective function that varies linearly only with some variables and nonlinearly with the remaining variables. The proposed MOGA application allows finding a Pareto frontier of optimal solutions, which is compared with the frontier obtained by solving the same problem with Integer Linear Programming (ILP), where piecewise constant contributions are linearly approximated. The two found curves represent, respectively, the upper and the lower limit of the region including the real Pareto curve. Both the genetic optimisation and the ILP models are applied under structural constraints to a case study describing the distribution chain of a large enterprise of southern Italy producing consumer goods. © 2012 Taylor & Francis.

  @ARTICLE{Bevilacqua20121139,
  author = {Bevilacqua, Vitoantonio and Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Sciancalepore, Fabio},
  title = {Strategic design and multi-objective optimisation of distribution networks based on genetic algorithms},
  year = {2012},
  journal = {International Journal of Computer Integrated Manufacturing},
  volume = {25},
  number = {12},
  pages = {1139 – 1150},
  doi = {10.1080/0951192X.2012.684719},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875891154&doi=10.1080%2f0951192X.2012.684719&partnerID=40&md5=93f7eb805aa3693cb435b50e08437218},
  abstract = {The paper addresses the optimal design of distribution networks (DNs). Considering a distributed system composed of stages connected by material links labelled with suitable performance indices, a procedure employing multiobjective genetic algorithms (MOGAs) is presented to select the optimal DN configuration. The paper enhances a deterministic procedure for DN strategic configuration by employing MOGACOP, a real-valued chromosome MOGA that can be applied to the case of constrained nonlinear function. The main MOGA characteristics are the presence of three populations: two reference sets of individuals satisfying all constraints, namely, a set of Pareto optimal individuals (frontier population) and a set of individuals covering the previous population (archive population), together with a search set which, on the contrary, includes individuals that are allowed to not satisfy all constraints (laboratory population). MOGACOP allows solving the DN design nonlinear problem, which exhibits a multi-objective function that varies linearly only with some variables and nonlinearly with the remaining variables. The proposed MOGA application allows finding a Pareto frontier of optimal solutions, which is compared with the frontier obtained by solving the same problem with Integer Linear Programming (ILP), where piecewise constant contributions are linearly approximated. The two found curves represent, respectively, the upper and the lower limit of the region including the real Pareto curve. Both the genetic optimisation and the ILP models are applied under structural constraints to a case study describing the distribution chain of a large enterprise of southern Italy producing consumer goods. © 2012 Taylor & Francis.},
  author_keywords = {Distribution network; Integer linear programming; Multi-objective genetic algorithms; Optimisation; Supply chain},
  keywords = {Chromosomes; Electric power distribution; Genetic algorithms; Integer programming; Multiobjective optimization; Optimal systems; Pareto principle; Supply chains; Integer Linear Programming; Multi-objective functions; Multi-objective genetic algorithm; Nonlinear functions; Optimisations; Performance indices; Piece-wise constants; Structural constraints; Distribution of goods},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 23}
  }

• Costantino, N., Dotoli, M., Falagario, M. & Sciancalepore, F. (2012) Balancing the additional costs of purchasing and the vendor set dimension to reduce public procurement costs. IN Journal of Purchasing and Supply Management, 18.189 – 198. doi:10.1016/j.pursup.2012.08.001
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the reduction of the total cost of purchasing in public procurement, focusing on tenders called for in the European Union and awarded by the Lowest Price (LP) criterion. Taking into account the main characteristic features of governmental purchasing (competition, prescribed procedures, and transparency) and building upon the related contributions in the literature, we present a probabilistic approach for evaluating and limiting the total cost of purchasing in public tenders awarded according to the LP criterion. The presented framework includes the evaluation of the so-called additional costs of purchasing (ACP), a part of the transaction cost that is typically considered in the related literature from a private organization perspective only. The approach can be applied to a generic transaction in any public tender issued according to the European legislation with the LP criterion. Considering the real case study of the public tender for maintenance works on a municipal sport facility in Bari (Italy), we take into account the costs of both transaction counterparts, i.e., the ACP regarding the contracting authority and those related to the firms involved in the tender. Applying the model to the case study, we underline the relevance of ACP for public tenders and show that, by inviting a suitable number of bidders to participate in the call, it is possible to save money both for the contracting authority and the involved competitors. © 2012 Elsevier Ltd.

  @ARTICLE{Costantino2012189,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Sciancalepore, Fabio},
  title = {Balancing the additional costs of purchasing and the vendor set dimension to reduce public procurement costs},
  year = {2012},
  journal = {Journal of Purchasing and Supply Management},
  volume = {18},
  number = {3},
  pages = {189 – 198},
  doi = {10.1016/j.pursup.2012.08.001},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870475495&doi=10.1016%2fj.pursup.2012.08.001&partnerID=40&md5=23cde4dd3b96e37858b9a0a3e6661e65},
  abstract = {The paper addresses the reduction of the total cost of purchasing in public procurement, focusing on tenders called for in the European Union and awarded by the Lowest Price (LP) criterion. Taking into account the main characteristic features of governmental purchasing (competition, prescribed procedures, and transparency) and building upon the related contributions in the literature, we present a probabilistic approach for evaluating and limiting the total cost of purchasing in public tenders awarded according to the LP criterion. The presented framework includes the evaluation of the so-called additional costs of purchasing (ACP), a part of the transaction cost that is typically considered in the related literature from a private organization perspective only. The approach can be applied to a generic transaction in any public tender issued according to the European legislation with the LP criterion. Considering the real case study of the public tender for maintenance works on a municipal sport facility in Bari (Italy), we take into account the costs of both transaction counterparts, i.e., the ACP regarding the contracting authority and those related to the firms involved in the tender. Applying the model to the case study, we underline the relevance of ACP for public tenders and show that, by inviting a suitable number of bidders to participate in the call, it is possible to save money both for the contracting authority and the involved competitors. © 2012 Elsevier Ltd.},
  author_keywords = {Additional costs of purchasing; Public procurement; Supplier selection; Tendering costs},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 24}
  }

2011

• Dotoli, M., Fanti, M. P. & Iacobellis, G. (2011) A freeway traffic control model by first order hybrid Petri nets IN IEEE International Conference on Automation Science and Engineering., 425 – 431. doi:10.1109/CASE.2011.6042526
  [BibTeX] [Abstract] [Download PDF]

  The paper proposes a model for real time control of freeways by ramp metering, an emerging technique for efficient freeway management. A modular framework based on first order hybrid Petri nets models the vehicle flows by a first order fluid approximation. Moreover, the lane interruptions and the signal timing plan controlling on-ramps are described by the discrete event dynamics using timed Petri nets. The proposed formalism enables the network designer to choose suitable ramp metering control signals in order to maximize the traffic flow by optimizing a suitable objective function. The optimal mode of operation is performed based on the state knowledge of the obtained linear discrete-time, time-varying state variable model of the freeway to react to unpredictable events such as the blocking of a lane due to an accident or to work in progress. The proposed model is applied to a case study to show its effectiveness. © 2011 IEEE.

  @CONFERENCE{Dotoli2011425,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio},
  title = {A freeway traffic control model by first order hybrid Petri nets},
  year = {2011},
  journal = {IEEE International Conference on Automation Science and Engineering},
  pages = {425 – 431},
  doi = {10.1109/CASE.2011.6042526},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-82455171715&doi=10.1109%2fCASE.2011.6042526&partnerID=40&md5=0eacc79a854cfd9ea5705a33dd71e12c},
  abstract = {The paper proposes a model for real time control of freeways by ramp metering, an emerging technique for efficient freeway management. A modular framework based on first order hybrid Petri nets models the vehicle flows by a first order fluid approximation. Moreover, the lane interruptions and the signal timing plan controlling on-ramps are described by the discrete event dynamics using timed Petri nets. The proposed formalism enables the network designer to choose suitable ramp metering control signals in order to maximize the traffic flow by optimizing a suitable objective function. The optimal mode of operation is performed based on the state knowledge of the obtained linear discrete-time, time-varying state variable model of the freeway to react to unpredictable events such as the blocking of a lane due to an accident or to work in progress. The proposed model is applied to a case study to show its effectiveness. © 2011 IEEE.},
  keywords = {Highway traffic control; Optimization; Petri nets; Real time control; Timing circuits; Control model; Discrete event dynamics; Discrete-time; First order; First-order hybrid Petri nets; Fluid approximation; Freeway management; Freeway traffic; Modular framework; Network designer; Objective functions; Optimal modes; Ramp metering; Ramp metering control; Signal timing plan; State-variable model; Time varying; Timed Petri Net; Traffic flow; Vehicle flow; Work in progress; Highway planning},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 13}
  }

• Dotoli, M., Pia Fanti, M., Mangini, A. M. & Ukovich, W. (2011) Identification of the unobservable behaviour of industrial automation systems by Petri nets. IN Control Engineering Practice, 19.958 – 966. doi:10.1016/j.conengprac.2010.09.004
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses the problem of identifying the model of the unobservable behaviour of discrete event systems in the industrial automation sector. Assuming that the fault-free system structure and dynamics are known, the paper proposes an algorithm that monitors the system on-line, storing the occurred observable event sequence and the corresponding reached states. At each event observation, the algorithm checks whether some unobservable events have occurred on the basis of the knowledge of the Petri net (PN) modelling the nominal system behaviour and the knowledge of the current PN marking. By defining and solving some integer linear programming problems, the algorithm decides whether it is necessary to introduce some unobservable (silent) transitions in the PN model and provides a PN structure that is consistent with the observed event string. A case study describing an industrial automation system shows the efficiency and the applicability of the proposed algorithm. © 2010 Elsevier Ltd.

  @ARTICLE{Dotoli2011958,
  author = {Dotoli, Mariagrazia and Pia Fanti, Maria and Mangini, Agostino M. and Ukovich, Walter},
  title = {Identification of the unobservable behaviour of industrial automation systems by Petri nets},
  year = {2011},
  journal = {Control Engineering Practice},
  volume = {19},
  number = {9},
  pages = {958 – 966},
  doi = {10.1016/j.conengprac.2010.09.004},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960892257&doi=10.1016%2fj.conengprac.2010.09.004&partnerID=40&md5=815e201639c50a3802273cce4a66a803},
  abstract = {This paper addresses the problem of identifying the model of the unobservable behaviour of discrete event systems in the industrial automation sector. Assuming that the fault-free system structure and dynamics are known, the paper proposes an algorithm that monitors the system on-line, storing the occurred observable event sequence and the corresponding reached states. At each event observation, the algorithm checks whether some unobservable events have occurred on the basis of the knowledge of the Petri net (PN) modelling the nominal system behaviour and the knowledge of the current PN marking. By defining and solving some integer linear programming problems, the algorithm decides whether it is necessary to introduce some unobservable (silent) transitions in the PN model and provides a PN structure that is consistent with the observed event string. A case study describing an industrial automation system shows the efficiency and the applicability of the proposed algorithm. © 2010 Elsevier Ltd.},
  author_keywords = {Discrete event systems; Identification algorithms; Industrial automation systems; Integer programming; Modelling; Petri nets},
  keywords = {Algorithms; Automation; Enterprise resource planning; Industry; Integer programming; Petri nets; Event sequence; Identification algorithms; Industrial automation; Industrial automation system; Integer Linear Programming; Modelling; Nominal system; P-n structure; PN models; System structures; Unobservable; Mathematical models},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 51}
  }

• Boschian, V., Dotoli, M., Fanti, M. P., Iacobellis, G. & Ukovich, W. (2011) A metamodeling approach to the management of intermodal transportation networks. IN IEEE Transactions on Automation Science and Engineering, 8.457 – 469. doi:10.1109/TASE.2010.2090870
  [BibTeX] [Abstract] [Download PDF]

  The paper specifies an Integrated System (IS) devoted to the management of Intermodal Transportation Networks (ITNs) to take both tactical decisions, i.e., in an offline mode, and operational decisions, i.e., in real-time. Both the resulting IS structures rely on a closed-loop approach that is able to tune the choices with the current system conditions. In either case, the core of the presented IS are a reference model and a simulation module. In particular, the reference model uses information from the real system, obtained by modern Information and Communication Technologies (ICTs) and the simulation module evaluates the impact of the management decisions. In order to obtain a systematic model suitable to describe a generic ITN, the paper proposes a metamodeling approach that describes in a thorough and detailed way the structure and the behavior of ITNs. Moreover, the metamodeling procedure is a top-down technique based on the well-known Unified Modeling Language (UML), a graphic and textual formalism able to describe systems from structural and behavioral viewpoints. In order to show the IS application at the tactical decision level, the paper specifies the IS for an ITN case study that is constituted by the port of Trieste (Italy) and the inland terminal of Gorizia (Italy). The results show how the IS can improve the performance of the ITN by applying ICT tools and information-based services. © 2011 IEEE.

  @ARTICLE{Boschian2011457,
  author = {Boschian, Valentina and Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio and Ukovich, Walter},
  title = {A metamodeling approach to the management of intermodal transportation networks},
  year = {2011},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {8},
  number = {3},
  pages = {457 – 469},
  doi = {10.1109/TASE.2010.2090870},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960116582&doi=10.1109%2fTASE.2010.2090870&partnerID=40&md5=b5a3b21157365d4fe27cdd8291be8c20},
  abstract = {The paper specifies an Integrated System (IS) devoted to the management of Intermodal Transportation Networks (ITNs) to take both tactical decisions, i.e., in an offline mode, and operational decisions, i.e., in real-time. Both the resulting IS structures rely on a closed-loop approach that is able to tune the choices with the current system conditions. In either case, the core of the presented IS are a reference model and a simulation module. In particular, the reference model uses information from the real system, obtained by modern Information and Communication Technologies (ICTs) and the simulation module evaluates the impact of the management decisions. In order to obtain a systematic model suitable to describe a generic ITN, the paper proposes a metamodeling approach that describes in a thorough and detailed way the structure and the behavior of ITNs. Moreover, the metamodeling procedure is a top-down technique based on the well-known Unified Modeling Language (UML), a graphic and textual formalism able to describe systems from structural and behavioral viewpoints. In order to show the IS application at the tactical decision level, the paper specifies the IS for an ITN case study that is constituted by the port of Trieste (Italy) and the inland terminal of Gorizia (Italy). The results show how the IS can improve the performance of the ITN by applying ICT tools and information-based services. © 2011 IEEE.},
  author_keywords = {Management; modeling; simulation; transportation},
  keywords = {Computer simulation; Decision making; Decision support systems; Information management; Information technology; Mathematical models; Models; Network management; Transportation; Unified Modeling Language; Closed-loop; Current system; ICT-tools; Information and communication technologies; Information based services; Inland Terminals; Integrated systems; Management decisions; Metamodeling; Offline modes; Operational decisions; Real systems; Reference models; simulation; Simulation modules; Systematic models; Tactical decisions; Topdown; Trieste; Intermodal transportation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 53}
  }

• Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P., Mangini, A. M. & Sciancalepore, F. (2011) Supplier selection in the public procurement sector via a data envelopment analysis approach IN 2011 19th Mediterranean Conference on Control and Automation, MED 2011., 236 – 241. doi:10.1109/MED.2011.5983149
  [BibTeX] [Abstract] [Download PDF]

  The paper deals with the strategic issue of the supplier selection in the public procurement context. We consider the Data Envelopment Analysis (DEA), the most widespread method for supplier selection in the literature for private organizations. We modify the so-called cross-efficiency DEA approach and apply the method to supplier selection in a public tender, taking into account transparency and rating requirements. The presented approach is applied to a real case study in order to evaluate its effectiveness, while discussing it with respect to the cross-efficiency DEA method. © 2011 IEEE.

  @CONFERENCE{Costantino2011236,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Fanti, Maria Pia and Mangini, Agostino Marcello and Sciancalepore, Fabio},
  title = {Supplier selection in the public procurement sector via a data envelopment analysis approach},
  year = {2011},
  journal = {2011 19th Mediterranean Conference on Control and Automation, MED 2011},
  pages = {236 – 241},
  doi = {10.1109/MED.2011.5983149},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052390458&doi=10.1109%2fMED.2011.5983149&partnerID=40&md5=7c3f328a621048ae0e81f6da20b08372},
  abstract = {The paper deals with the strategic issue of the supplier selection in the public procurement context. We consider the Data Envelopment Analysis (DEA), the most widespread method for supplier selection in the literature for private organizations. We modify the so-called cross-efficiency DEA approach and apply the method to supplier selection in a public tender, taking into account transparency and rating requirements. The presented approach is applied to a real case study in order to evaluate its effectiveness, while discussing it with respect to the cross-efficiency DEA method. © 2011 IEEE.},
  author_keywords = {Data Envelopment Analysis; input criteria; output criteria; supplier selection; Supply chains},
  keywords = {Supply chains; Cross-efficiency; input criteria; output criteria; Private organizations; Public procurement; Public tender; Strategic issues; Supplier selection; Data envelopment analysis},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 9}
  }

• Bevilacqua, V., Dotoli, M., Falagario, M., Sciancalepore, F., D’Ambruoso, D., Saladino, S. & Scaramuzzi, R. (2011) A multi-objective genetic optimization technique for the strategic design of distribution networks. IN Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6839 LNAI.243 – 250. doi:10.1007/978-3-642-25944-9_32
  [BibTeX] [Abstract] [Download PDF]

  We address the optimal design of a Distribution Network (DN), presenting a procedure employing Multi-Objective Genetic Algorithms (MOGA) to select the (sub) optimal DN configuration. Using multi-objective genetic optimization allows solving a nonlinear design problem with piecewise constant contributions in addition to linear ones. The MOGA application allows finding a Pareto frontier of (sub) optimal solutions, which is compared with the frontier obtained solving the same problem with linear programming, where piecewise constant contributions are linearly approximated. The two curves represent, respectively, the upper and the lower limit of the region including the real Pareto curve. Both the genetic optimization model and the linear programming are applied under structural constraints to a case study describing the DN of an Italian enterprise. © 2012 Springer-Verlag.

  @ARTICLE{Bevilacqua2011243,
  author = {Bevilacqua, Vitoantonio and Dotoli, Mariagrazia and Falagario, Marco and Sciancalepore, Fabio and D'Ambruoso, Dario and Saladino, Stefano and Scaramuzzi, Rocco},
  title = {A multi-objective genetic optimization technique for the strategic design of distribution networks},
  year = {2011},
  journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
  volume = {6839 LNAI},
  pages = {243 – 250},
  doi = {10.1007/978-3-642-25944-9_32},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84855649344&doi=10.1007%2f978-3-642-25944-9_32&partnerID=40&md5=4044f12c0adc8b6feca42442cd2b6d10},
  abstract = {We address the optimal design of a Distribution Network (DN), presenting a procedure employing Multi-Objective Genetic Algorithms (MOGA) to select the (sub) optimal DN configuration. Using multi-objective genetic optimization allows solving a nonlinear design problem with piecewise constant contributions in addition to linear ones. The MOGA application allows finding a Pareto frontier of (sub) optimal solutions, which is compared with the frontier obtained solving the same problem with linear programming, where piecewise constant contributions are linearly approximated. The two curves represent, respectively, the upper and the lower limit of the region including the real Pareto curve. Both the genetic optimization model and the linear programming are applied under structural constraints to a case study describing the DN of an Italian enterprise. © 2012 Springer-Verlag.},
  keywords = {Computation theory; Design; Intelligent computing; Linear programming; Optimal systems; Distribution network; Genetic optimization; Lower limits; Multi objective; Multi-objective genetic algorithm; Non-linear design; Optimal design; Optimal solutions; Pareto curve; Pareto frontiers; Piecewise constant; Strategic design; Structural constraints; Multiobjective optimization},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P., Mangini, A. M., Sciancalepore, F. & Ukovich, W. (2011) A fuzzy programming approach for the strategic design of distribution networks IN IEEE International Conference on Automation Science and Engineering., 66 – 71. doi:10.1109/CASE.2011.6042483
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the optimal design of the last branch of the supply chain, i.e., the Distribution Network (DN). We extend a deterministic optimization model previously proposed by the authors, using fuzzy numbers and fuzzy logic to take into account uncertainty in the DN model and in the DN design. Hence, a procedure employing digraph modeling and fuzzy mixed integer linear programming is presented to select the optimal DN configuration. To show the method effectiveness, the optimization model is applied to a case study. © 2011 IEEE.

  @CONFERENCE{Costantino201166,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Fanti, Maria Pia and Mangini, Agostino M. and Sciancalepore, Fabio and Ukovich, Walter},
  title = {A fuzzy programming approach for the strategic design of distribution networks},
  year = {2011},
  journal = {IEEE International Conference on Automation Science and Engineering},
  pages = {66 – 71},
  doi = {10.1109/CASE.2011.6042483},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-82455162802&doi=10.1109%2fCASE.2011.6042483&partnerID=40&md5=2f1963aa6b253c62377cba9a0b025009},
  abstract = {The paper addresses the optimal design of the last branch of the supply chain, i.e., the Distribution Network (DN). We extend a deterministic optimization model previously proposed by the authors, using fuzzy numbers and fuzzy logic to take into account uncertainty in the DN model and in the DN design. Hence, a procedure employing digraph modeling and fuzzy mixed integer linear programming is presented to select the optimal DN configuration. To show the method effectiveness, the optimization model is applied to a case study. © 2011 IEEE.},
  keywords = {Design; Embedded systems; Fuzzy sets; Integer programming; Linear programming; Mathematical models; Optimization; Supply chains; Deterministic optimization; Distribution network; Fuzzy numbers; Fuzzy programming; Mixed integer linear programming; Optimal design; Optimization models; Strategic design; Fuzzy logic},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 18}
  }

• Costantino, N., Dotoli, M., Falagario, M. & Sciancalepore, F. (2011) A model using Data Envelopment Analysis for the cross evaluation of suppliers under uncertainty IN KMIS 2011 – Proceedings of the International Conference on Knowledge Management and Information Sharing., 152 – 157.
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses one of the key objectives of the purchasing function of a supply chain, i.e., the optimal selection of suppliers. We present a novel methodology that integrates the well-known cross-efficiency evaluation called Data Envelopment Analysis (DEA) and the Monte Carlo approach, to manage supplier selection considering uncertainty in the supply process, e.g. evaluating potential suppliers. The model allows to distinguish among several suppliers, overcoming the limitation of the traditional DEA method of not distinguishing among efficient suppliers. Moreover, the technique is able to classify suppliers with uncertain performance. The method is applied to the selection of suppliers of a Southern Italy SME.

  @CONFERENCE{Costantino2011152,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Sciancalepore, Fabio},
  title = {A model using Data Envelopment Analysis for the cross evaluation of suppliers under uncertainty},
  year = {2011},
  journal = {KMIS 2011 - Proceedings of the International Conference on Knowledge Management and Information Sharing},
  pages = {152 – 157},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84862215445&partnerID=40&md5=9afb90897b8c7deeaf28d4b6f43668b9},
  abstract = {The paper addresses one of the key objectives of the purchasing function of a supply chain, i.e., the optimal selection of suppliers. We present a novel methodology that integrates the well-known cross-efficiency evaluation called Data Envelopment Analysis (DEA) and the Monte Carlo approach, to manage supplier selection considering uncertainty in the supply process, e.g. evaluating potential suppliers. The model allows to distinguish among several suppliers, overcoming the limitation of the traditional DEA method of not distinguishing among efficient suppliers. Moreover, the technique is able to classify suppliers with uncertain performance. The method is applied to the selection of suppliers of a Southern Italy SME.},
  author_keywords = {Business intelligence; Data Envelopment Analysis; Monte Carlo method; Supplier evaluation; Uncertainty},
  keywords = {Competitive intelligence; Information analysis; Knowledge management; Management science; Monte Carlo methods; Supply chains; Cross evaluation; Cross-efficiency evaluation; Key objective; Monte Carlo approach; Novel methodology; Optimal selection; Southern Italy; Supplier Evaluations; Supplier selection; Supply process; Uncertainty; Data envelopment analysis},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2011) A fault monitor for automated manufacturing systems using a hybrid Petri nets formalism. IN Transactions of the Institute of Measurement and Control, 33.149 – 167. doi:10.1177/0142331208095677
  [BibTeX] [Abstract] [Download PDF]

  Fault monitoring is an essential requirement for safety and reliability of industrial systems. The paper presents a novel event-based online monitoring technique for automated manufacturing systems, ensuring timely and accurate detection of system failures. The monitor model is based on first-order hybrid Petri nets, ie, Petri nets that make use of first-order fluid approximation. The proposed fault analysis technique relies on a modular framework, so that elementary monitors can be connected with other monitors to check more complex systems while avoiding the state—space explosion problem. In addition, the presented monitor detects system faults as soon as possible, before the maximum execution time assigned to each task. Several examples and an application to an automated manufacturing system proposed in the related literature enlighten the simplicity and modularity of the technique. © 2011, The Institute of Measurement and Control. All rights reserved.

  @ARTICLE{Dotoli2011149,
  author = {Dotoli, M. and Fanti, M.P. and Mangini, A.M.},
  title = {A fault monitor for automated manufacturing systems using a hybrid Petri nets formalism},
  year = {2011},
  journal = {Transactions of the Institute of Measurement and Control},
  volume = {33},
  number = {1},
  pages = {149 – 167},
  doi = {10.1177/0142331208095677},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952018267&doi=10.1177%2f0142331208095677&partnerID=40&md5=cd6895ba069c273a8b8dea22e607b34c},
  abstract = {Fault monitoring is an essential requirement for safety and reliability of industrial systems. The paper presents a novel event-based online monitoring technique for automated manufacturing systems, ensuring timely and accurate detection of system failures. The monitor model is based on first-order hybrid Petri nets, ie, Petri nets that make use of first-order fluid approximation. The proposed fault analysis technique relies on a modular framework, so that elementary monitors can be connected with other monitors to check more complex systems while avoiding the state—space explosion problem. In addition, the presented monitor detects system faults as soon as possible, before the maximum execution time assigned to each task. Several examples and an application to an automated manufacturing system proposed in the related literature enlighten the simplicity and modularity of the technique. © 2011, The Institute of Measurement and Control. All rights reserved.},
  author_keywords = {automated manufacturing systems; discrete event systems; fault detection; fault monitoring; hybrid Petri nets},
  keywords = {Accident prevention; Automation; Discrete event simulation; Fault detection; Manufacture; Online systems; Petri nets; Automated manufacturing systems; Fault monitoring; First-order hybrid Petri nets; Fluid approximation; Hybrid Petri net; Industrial systems; Online monitoring technique; State-space explosion; Monitoring},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

• Dotoli, M., Fanti, M. P., Rotunno, G. & Ukovich, W. (2011) A lean manufacturing procedure using value stream mapping and the analytic hierarchy process IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 1193 – 1198. doi:10.1109/ICSMC.2011.6083860
  [BibTeX] [Abstract] [Download PDF]

  We present a novel lean manufacturing procedure relying on the Value Stream Mapping (VSM) tool and the Analytic Hierarchy Process (AHP) technique. The procedure is iterative and hierarchical. Starting from a detailed description of the manufacturing process by the Unified Modeling Language (UML), the VSM graphical approach allows the identification of non-value adding activities, and the AHP technique leads to a ranking of such system anomalies. The further application of the VSM tool produces an overall picture of the desired manufacturing system, and the UML framework allows to describe in detail the updated system activities. An application of the procedure to a real case study shows its effectiveness. © 2011 IEEE.

  @CONFERENCE{Dotoli20111193,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Rotunno, Giuliana and Ukovich, Walter},
  title = {A lean manufacturing procedure using value stream mapping and the analytic hierarchy process},
  year = {2011},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  pages = {1193 – 1198},
  doi = {10.1109/ICSMC.2011.6083860},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-83755183338&doi=10.1109%2fICSMC.2011.6083860&partnerID=40&md5=843a636531caf0465d157f9126def8b1},
  abstract = {We present a novel lean manufacturing procedure relying on the Value Stream Mapping (VSM) tool and the Analytic Hierarchy Process (AHP) technique. The procedure is iterative and hierarchical. Starting from a detailed description of the manufacturing process by the Unified Modeling Language (UML), the VSM graphical approach allows the identification of non-value adding activities, and the AHP technique leads to a ranking of such system anomalies. The further application of the VSM tool produces an overall picture of the desired manufacturing system, and the UML framework allows to describe in detail the updated system activities. An application of the procedure to a real case study shows its effectiveness. © 2011 IEEE.},
  author_keywords = {Analytic Hierarchy Process; Lean Manufacturing; Unified Modelling Language; Value Stream Mapping},
  keywords = {Agile manufacturing systems; Analytic hierarchy process; Cybernetics; Hierarchical systems; Mapping; Graphical approach; Lean manufacturing; Manufacturing process; Manufacturing system; Value stream mapping; Unified Modeling Language},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 5}
  }

2010

• Boschian, V., Ukovich, W., Dotoli, M., Fanti, M. P. & Iacobellis, G. (2010) A metamodeling technique for managing intermodal transportation networks IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 209 – 214. doi:10.1109/ICSMC.2010.5642236
  [BibTeX] [Abstract] [Download PDF]

  The paper specifies an Integrated System (IS) devoted to efficient management and control of Intermodal Transportation Networks (ITN). The IS is designed to take both tactical decisions, in an off-line mode, and operational decisions, in real time. Both the resulting IS structures rely on a closed loop approach tuning decisions with the current system conditions. In either case, the IS core is a reference model using information from the real system, obtained by modern Information and Communication Technologies (ICT) tools, for ITN efficient planning and management purposes. To obtain a systematic model suitable to describing generic ITN, the reference model relies on a metamodeling approach that allows the thorough and detailed description of the ITN structure and behavior. The proposed metamodeling procedure is a top-down approach based on the Unified Modeling Language, a graphic and textual formalism for representing systems structure and behavior. ©2010 IEEE.

  @CONFERENCE{Boschian2010209,
  author = {Boschian, Valentina and Ukovich, Walter and Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio},
  title = {A metamodeling technique for managing intermodal transportation networks},
  year = {2010},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  pages = {209 – 214},
  doi = {10.1109/ICSMC.2010.5642236},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78751549508&doi=10.1109%2fICSMC.2010.5642236&partnerID=40&md5=b1edf63b1e04ce6b731fd89670d147db},
  abstract = {The paper specifies an Integrated System (IS) devoted to efficient management and control of Intermodal Transportation Networks (ITN). The IS is designed to take both tactical decisions, in an off-line mode, and operational decisions, in real time. Both the resulting IS structures rely on a closed loop approach tuning decisions with the current system conditions. In either case, the IS core is a reference model using information from the real system, obtained by modern Information and Communication Technologies (ICT) tools, for ITN efficient planning and management purposes. To obtain a systematic model suitable to describing generic ITN, the reference model relies on a metamodeling approach that allows the thorough and detailed description of the ITN structure and behavior. The proposed metamodeling procedure is a top-down approach based on the Unified Modeling Language, a graphic and textual formalism for representing systems structure and behavior. ©2010 IEEE.},
  author_keywords = {Discrete event simulation; Information and communication technologies; Intermodal transportation networks; Management; Modeling; Unified modelling language},
  keywords = {Computer simulation languages; Cybernetics; Discrete event simulation; Integrated optics; Mathematical models; Models; Network management; Planning; Transportation; Unified Modeling Language; Closed loops; Current system; Efficient planning; Information and Communication Technologies; Integrated systems; Meta-modeling technique; Metamodeling; Modeling; Offline modes; Operational decisions; Real systems; Real time; Reference models; Systematic models; Systems Structure; Tactical decisions; Top-down approach; Unified modelling language; Intermodal transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Boschian, V., Dotoli, M., Fanti, M. P., Iacobellis, G. & Ukovich, W. (2010) A metamodelling approach for performance evaluation of intermodal transportation networks. IN European Transport – Trasporti Europei, .100 – 113.
  [BibTeX] [Abstract] [Download PDF]

  The paper proposes a metamodelling procedure devoted to provide a reference model to be used by decision makers in the performance evaluation of Intermodal Transportation Network (ITN). In order to obtain a generic model describing a nonspecific ITN from the structural and behavioural point of view, the metamodelling approach consists in applying a top down and modular procedure. The model is specified by the well known Unified Modelling Language (UML), a graphic and textual modelling formalism intended to describe systems from structural and dynamics viewpoints. Hence, the paper models a generic ITN starting from the network description and shows by a case study the metamodel of one of the most important nodes that compose it: the port subsystem. Moreover, the case study model is translated in a simulation software and the performance measures obtained by the simulation results are shown.

  @ARTICLE{Boschian2010100,
  author = {Boschian, Valentina and Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio and Ukovich, Walter},
  title = {A metamodelling approach for performance evaluation of intermodal transportation networks},
  year = {2010},
  journal = {European Transport - Trasporti Europei},
  number = {46},
  pages = {100 – 113},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960590476&partnerID=40&md5=080eb60a70e81223db1c885881269c8a},
  abstract = {The paper proposes a metamodelling procedure devoted to provide a reference model to be used by decision makers in the performance evaluation of Intermodal Transportation Network (ITN). In order to obtain a generic model describing a nonspecific ITN from the structural and behavioural point of view, the metamodelling approach consists in applying a top down and modular procedure. The model is specified by the well known Unified Modelling Language (UML), a graphic and textual modelling formalism intended to describe systems from structural and dynamics viewpoints. Hence, the paper models a generic ITN starting from the network description and shows by a case study the metamodel of one of the most important nodes that compose it: the port subsystem. Moreover, the case study model is translated in a simulation software and the performance measures obtained by the simulation results are shown.},
  author_keywords = {Discrete event simulation; Intermodal transportation networks; Modeling; Performance evaluation; Uml},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Costantino, N., Dotoli, M., Falagario, M., Pia Fanti, M., Marcello Mangini, A., Sciancalepore, F. & Ukovich, W. (2010) A model for the strategic design of Distribution Networks IN 2010 IEEE International Conference on Automation Science and Engineering, CASE 2010., 406 – 411. doi:10.1109/COASE.2010.5584706
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the optimal design of the last branch of the supply chain, i.e., the Distribution Network (DN), starting from manufacturers till the retailers. Considering a distributed system composed of different stages connected by material links labeled with suitable performance indices, a procedure employing digraph modeling and mixed integer linear programming is presented to select the (sub)optimal DN configuration. The optimization model is applied under structural constraints to a case study describing the distribution chain of a large enterprise of southern Italy producing consumer goods. The problem solution provides different structures allowing the improvement of the DN flexibility and performance. © 2010 IEEE.

  @CONFERENCE{Costantino2010406,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Pia Fanti, Maria and Marcello Mangini, Agostino and Sciancalepore, Fabio and Ukovich, Walter},
  title = {A model for the strategic design of Distribution Networks},
  year = {2010},
  journal = {2010 IEEE International Conference on Automation Science and Engineering, CASE 2010},
  pages = {406 – 411},
  doi = {10.1109/COASE.2010.5584706},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78149431454&doi=10.1109%2fCOASE.2010.5584706&partnerID=40&md5=d75e6656395f003e11f71d3a96fe06ec},
  abstract = {The paper addresses the optimal design of the last branch of the supply chain, i.e., the Distribution Network (DN), starting from manufacturers till the retailers. Considering a distributed system composed of different stages connected by material links labeled with suitable performance indices, a procedure employing digraph modeling and mixed integer linear programming is presented to select the (sub)optimal DN configuration. The optimization model is applied under structural constraints to a case study describing the distribution chain of a large enterprise of southern Italy producing consumer goods. The problem solution provides different structures allowing the improvement of the DN flexibility and performance. © 2010 IEEE.},
  keywords = {Distributed computer systems; Distributed parameter networks; Embedded systems; Integer programming; Optimization; Supply chains; Consumer Goods; Different structure; Distributed systems; Distribution chains; Distribution network; Mixed integer linear programming; Optimal design; Optimization models; Performance indices; Southern Italy; Strategic design; Structural constraints; Distribution of goods},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

• Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P., Mangini, A. M., Sciancalepore, F. & Ukovich, W. (2010) A model for the optimal design of the hospital drug distribution chain IN 2010 IEEE Workshop on Health Care Management, WHCM 2010.. doi:10.1109/WHCM.2010.5441281
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the optimal design of the last branch of the pharmaceutical supply chain, i.e., the Hospital Drug Distribution Chain (HDDC), starting from suppliers till the patients of a department. Considering a distributed healthcare system composed of different stages connected by medicine and information links labeled with suitable performance indices, a procedure employing digraph modeling and mixed integer linear programming is presented to select the (sub)optimal HDDC configuration. The optimization model is applied under structural constraints to a case study describing an Italian healthcare regional distribution chain. The problem solution provides different HDDC structures allowing the improvement of the healthcare supply chain flexibility and performance. ©2010 IEEE.

  @CONFERENCE{Costantino2010,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Fanti, Maria Pia and Mangini, Agostino Marcello and Sciancalepore, Fabio and Ukovich, Walter},
  title = {A model for the optimal design of the hospital drug distribution chain},
  year = {2010},
  journal = {2010 IEEE Workshop on Health Care Management, WHCM 2010},
  doi = {10.1109/WHCM.2010.5441281},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77952471175&doi=10.1109%2fWHCM.2010.5441281&partnerID=40&md5=15b29d270d1b264c1a87373be06efbe1},
  abstract = {The paper addresses the optimal design of the last branch of the pharmaceutical supply chain, i.e., the Hospital Drug Distribution Chain (HDDC), starting from suppliers till the patients of a department. Considering a distributed healthcare system composed of different stages connected by medicine and information links labeled with suitable performance indices, a procedure employing digraph modeling and mixed integer linear programming is presented to select the (sub)optimal HDDC configuration. The optimization model is applied under structural constraints to a case study describing an Italian healthcare regional distribution chain. The problem solution provides different HDDC structures allowing the improvement of the healthcare supply chain flexibility and performance. ©2010 IEEE.},
  author_keywords = {Hospital drug distribution system; Mixed integer linear programming; Optimization; Performance; Supply chain},
  keywords = {Health care; Hospitals; Integer programming; Linear programming; Linearization; Optimal systems; Supply chain management; Supply chains; Drug distribution; Health-care system; Information links; Mixed integer linear programming; Optimal design; Optimization models; Performance; Performance indices; Regional distribution; Structural constraints; Supply chain flexibility; Optimization},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 14}
  }

• Dotoli, M., Fanti, M. P., Iacobellis, G., Martino, L., Moretti, A. M. & Ukovich, W. (2010) Modeling and management of a hospital department via petri nets IN 2010 IEEE Workshop on Health Care Management, WHCM 2010.. doi:10.1109/WHCM.2010.5441248
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses the management and performance analysis of the pulmonology department of the general hospital of Bari, Italy, focusing on the department workflow and drug distribution system. To this aim, we present a discrete event system model which can be employed as a support for taking decisions regarding the information and automation integration in order to improve the drug procurement logistics and management. The model employs a timed Petri net framework to describe in a concise and detailed way the workflow in the pulmonology department, while considering various ordering and management policies of the department drug storehouse. ©2010 IEEE.

  @CONFERENCE{Dotoli2010,
  author = {Dotoli, M. and Fanti, M.P. and Iacobellis, G. and Martino, L. and Moretti, A.M. and Ukovich, W.},
  title = {Modeling and management of a hospital department via petri nets},
  year = {2010},
  journal = {2010 IEEE Workshop on Health Care Management, WHCM 2010},
  doi = {10.1109/WHCM.2010.5441248},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77952487555&doi=10.1109%2fWHCM.2010.5441248&partnerID=40&md5=aaff79342353c72b989c2d5bf7a45ec5},
  abstract = {This paper addresses the management and performance analysis of the pulmonology department of the general hospital of Bari, Italy, focusing on the department workflow and drug distribution system. To this aim, we present a discrete event system model which can be employed as a support for taking decisions regarding the information and automation integration in order to improve the drug procurement logistics and management. The model employs a timed Petri net framework to describe in a concise and detailed way the workflow in the pulmonology department, while considering various ordering and management policies of the department drug storehouse. ©2010 IEEE.},
  author_keywords = {Drug distribution system; Hospital management; Performance evaluation; Petri nets; Pharmacy storehouse inventory; Simulation},
  keywords = {Graph theory; Health care; Hospitals; Model structures; Petri nets; Automation integration; Discrete event systems; Drug distribution; Hospital management; Management policy; Performance analysis; Performance evaluation; Timed Petri Net; Management},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 27}
  }

• Dotoli, M., Fanti, M. P., Mangini, A. M., Stecco, G. & Ukovich, W. (2010) The impact of ICT on intermodal transportation systems: A modelling approach by Petri nets. IN Control Engineering Practice, 18.893 – 903. doi:10.1016/j.conengprac.2010.03.013
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the issues of modelling and managing Intermodal Transportation Systems (ITS) at the operational level, considering the impact of the new Information and Communication Technologies (ICT). ITS are regarded as discrete event systems and are modelled in a timed Petri net framework. In order to show the efficiency of the ITS modelling and controlling technique, the case study of the ferry terminal of Trieste (Italy) is considered. The results show that the approach can be employed to verify the potential of ICT for efficient real time management of ITS, and their impact on the ITS infrastructures. © 2010 Elsevier Ltd.

  @ARTICLE{Dotoli2010893,
  author = {Dotoli, Mariagrazia and Fanti, Maria P. and Mangini, Agostino M. and Stecco, Gabriella and Ukovich, Walter},
  title = {The impact of ICT on intermodal transportation systems: A modelling approach by Petri nets},
  year = {2010},
  journal = {Control Engineering Practice},
  volume = {18},
  number = {8},
  pages = {893 – 903},
  doi = {10.1016/j.conengprac.2010.03.013},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955096154&doi=10.1016%2fj.conengprac.2010.03.013&partnerID=40&md5=3b58bbe0be9d1738e325d3777889db99},
  abstract = {The paper addresses the issues of modelling and managing Intermodal Transportation Systems (ITS) at the operational level, considering the impact of the new Information and Communication Technologies (ICT). ITS are regarded as discrete event systems and are modelled in a timed Petri net framework. In order to show the efficiency of the ITS modelling and controlling technique, the case study of the ferry terminal of Trieste (Italy) is considered. The results show that the approach can be employed to verify the potential of ICT for efficient real time management of ITS, and their impact on the ITS infrastructures. © 2010 Elsevier Ltd.},
  author_keywords = {Discrete event systems; Information technology; Petri-nets; Simulation; Transportation},
  keywords = {Discrete event simulation; Graph theory; Information technology; Petri nets; Discrete event systems; New information and communication technologies; Operational level; Real-time management; Timed Petri Net; Trieste; Intermodal transportation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 54}
  }

• Dotoli, M. & Falagario, M. (2010) A hierarchical vendor selection optimization technique for multiple sourcing IN KMIS 2010 – Proceedings of the International Conference on Knowledge Management and Information Sharing., 195 – 200.
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses a crucial objective of the strategic function of purchasing in supply chains, i.e., vendor rating, proposing a hierarchical model for supplier business intelligence. A three-level optimization process for supplier selection in a multiple sourcing strategy context is proposed. First, the Data Envelopment Analysis, the most widespread method for supplier selection, is used to evaluate the efficiency of suppliers. Second, the well-known Analytic Hierarchy Process is applied to rank the efficient suppliers given by the previous step. Third, a linear programming problem is solved to find the quantities to order from each efficient supplier. We show the model effectiveness on a simulated case study of a C class component.

  @CONFERENCE{Dotoli2010195,
  author = {Dotoli, Mariagrazia and Falagario, Marco},
  title = {A hierarchical vendor selection optimization technique for multiple sourcing},
  year = {2010},
  journal = {KMIS 2010 - Proceedings of the International Conference on Knowledge Management and Information Sharing},
  pages = {195 – 200},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78751511213&partnerID=40&md5=a5baa3113c034c11adfad250157507ed},
  abstract = {The paper addresses a crucial objective of the strategic function of purchasing in supply chains, i.e., vendor rating, proposing a hierarchical model for supplier business intelligence. A three-level optimization process for supplier selection in a multiple sourcing strategy context is proposed. First, the Data Envelopment Analysis, the most widespread method for supplier selection, is used to evaluate the efficiency of suppliers. Second, the well-known Analytic Hierarchy Process is applied to rank the efficient suppliers given by the previous step. Third, a linear programming problem is solved to find the quantities to order from each efficient supplier. We show the model effectiveness on a simulated case study of a C class component.},
  author_keywords = {Analytic hierarchy process; Business intelligence; Data envelopment analysis; Decision support system; Linear programming; Supplier evaluation and selection; Supply chain management},
  keywords = {Analytic hierarchy process; Artificial intelligence; Computer simulation; Computer software selection and evaluation; Data envelopment analysis; Data handling; Decision making; Decision support systems; Hierarchical systems; Information dissemination; Information retrieval; Knowledge management; Linear programming; Management science; Optimization; Supply chains; Business intelligence; Data envelopment; Decision supports; Hierarchical model; Linear programming problem; Optimization process; Optimization techniques; Sourcing strategies; Supplier Evaluations; Supplier selection; Three-level; Vendor Selection; Supply chain management},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M., Falagario, M., Mangini, A. M. & Sciancalepore, F. (2010) A novel formulation of the DEA model for application to supplier selection IN Proceedings of the 15th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2010.. doi:10.1109/ETFA.2010.5749382
  [BibTeX] [Abstract] [Download PDF]

  The paper deals with a key objective of the strategic purchasing function in supply chain management, namely vendor evaluation and selection. We propose a novel formulation of the so-called Data Envelopment Analysis (DEA) technique that overcomes some known drawbacks of DEA in the application to supplier selection in the enterprise integration, New constraints are introduced in the DEA method in order to better mimic the buyer behavior. We call the resulting approach DEA-P (DEA Percentage) because it allows the decision maker to compare the different supplier evaluation criteria by assigning a percentage index expressing the importance of each criterion. A simulated case study demonstrates the effectiveness of the novel method for suppliers election optimization. This work was supported by the Cassa di Risparmio di Puglia Foundation. © 2010 IEEE.

  @CONFERENCE{Dotoli2010,
  author = {Dotoli, Mariagrazia and Falagario, Marco and Mangini, Agostino Marcello and Sciancalepore, Fabio},
  title = {A novel formulation of the DEA model for application to supplier selection},
  year = {2010},
  journal = {Proceedings of the 15th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2010},
  doi = {10.1109/ETFA.2010.5749382},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901232311&doi=10.1109%2fETFA.2010.5749382&partnerID=40&md5=971587839c2b59b1389545fb72a851b6},
  abstract = {The paper deals with a key objective of the strategic purchasing function in supply chain management, namely vendor evaluation and selection. We propose a novel formulation of the so-called Data Envelopment Analysis (DEA) technique that overcomes some known drawbacks of DEA in the application to supplier selection in the enterprise integration, New constraints are introduced in the DEA method in order to better mimic the buyer behavior. We call the resulting approach DEA-P (DEA Percentage) because it allows the decision maker to compare the different supplier evaluation criteria by assigning a percentage index expressing the importance of each criterion. A simulated case study demonstrates the effectiveness of the novel method for suppliers election optimization. This work was supported by the Cassa di Risparmio di Puglia Foundation. © 2010 IEEE.},
  author_keywords = {Data Envelopment Analysis; Enterprise integration; Mathematical programming; Supply Chain; Vendor rating},
  keywords = {Data envelopment analysis; Decision making; Factory automation; Mathematical programming; Supply chain management; Supply chains; Buyer behavior; Data envelopment analysis technique; Dea methods; Decision makers; Enterprise Integration; Key objective; Supplier Evaluations; Supplier selection; Data integration},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

2009

• Dotoli, M., Fanti, M. P., Mangini, A. M. & Ukovich, W. (2009) On-line fault diagnosis in a petri net framework IN 2009 IEEE International Conference on Automation Science and Engineering, CASE 2009., 42 – 47. doi:10.1109/COASE.2009.5234113
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the fault detection problem for discrete event systems modeled by Petri Nets (PN). Assuming that the PN structure and initial marking are known, faults are modeled by unobservable transitions. The paper recalls a previously proposed diagnoser that works online and employs an algorithm based on the definition and solution of some integer linear programming problems to decide whether the system behavior is normal or exhibits some possible faults. To reduce the on-line computational effort, we prove some results showing that if the unobservable subnet enjoys suitable properties, the algorithm solution may be obtained with low computational complexity. We characterize the properties that the PN modeling the system fault behavior has to fulfill and suitably modify the proposed diagnoser. © 2009 IEEE.

  @CONFERENCE{Dotoli200942,
  author = {Dotoli, Mariagrazia and Fanti, Maria P. and Mangini, Agostino M. and Ukovich, Walter},
  title = {On-line fault diagnosis in a petri net framework},
  year = {2009},
  journal = {2009 IEEE International Conference on Automation Science and Engineering, CASE 2009},
  pages = {42 – 47},
  doi = {10.1109/COASE.2009.5234113},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70449135193&doi=10.1109%2fCOASE.2009.5234113&partnerID=40&md5=4fc1b5cbc8fe6f5849f9c52a0af94f6e},
  abstract = {The paper addresses the fault detection problem for discrete event systems modeled by Petri Nets (PN). Assuming that the PN structure and initial marking are known, faults are modeled by unobservable transitions. The paper recalls a previously proposed diagnoser that works online and employs an algorithm based on the definition and solution of some integer linear programming problems to decide whether the system behavior is normal or exhibits some possible faults. To reduce the on-line computational effort, we prove some results showing that if the unobservable subnet enjoys suitable properties, the algorithm solution may be obtained with low computational complexity. We characterize the properties that the PN modeling the system fault behavior has to fulfill and suitably modify the proposed diagnoser. © 2009 IEEE.},
  keywords = {Computational complexity; Failure analysis; Fault detection; Graph theory; Integer programming; Linearization; Petri nets; Algorithm solution; Computational effort; Discrete event systems; Fault detection problem; Initial marking; Integer Linear Programming; On-line fault diagnosis; P-n structure; System behaviors; System faults; Unobservable; Mathematical models},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Fanti, M. P. & Dotoli, M. (2009) Foreword IN IFAC Proceedings Volumes (IFAC-PapersOnline)., IV.
  [BibTeX] [Download PDF]

  @CONFERENCE{Fanti2009IV,
  author = {Fanti, Maria Pia and Dotoli, Mariagrazia},
  title = {Foreword},
  year = {2009},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {2},
  number = {PART 1},
  pages = {IV},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960961136&partnerID=40&md5=e2662f7a82922814111aca585d977af6},
  type = {Editorial},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M., Fanti, M. P., Iacobellis, G., Stecco, G. & Ukovich, W. (2009) Performance analysis and management of an Automated Distribution Center IN IECON Proceedings (Industrial Electronics Conference)., 4371 – 4376. doi:10.1109/IECON.2009.5414907
  [BibTeX] [Abstract] [Download PDF]

  Fierce global competition, rapid market changes and short product life cycles originated the diffusion of automated warehousing systems. This paper focuses on the performance evaluation and management of an Automated Distribution Center (ADC), i.e., a specific and automated type of warehouse where storage of products is limited or non-existent and the core activity is the sorting operation. We consider a case study in the clothing factory and we model the ADC as a discrete event system by way of the UML formalism, a graphic and textual modeling language intended to describe systems from structural and dynamics viewpoints. The ADC is simulated in the well-known ARENA simulation software environment under several scenarios, in which different system parameters are considered, e.g. number of material handling operators, speeds of machines, dimensions of pallets etc. The employed approach enables us to successfully select crucial parameters in order to improve the ADC management. ©2009 IEEE.

  @CONFERENCE{Dotoli20094371,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio and Stecco, Gabriella and Ukovich, Walter},
  title = {Performance analysis and management of an Automated Distribution Center},
  year = {2009},
  journal = {IECON Proceedings (Industrial Electronics Conference)},
  pages = {4371 – 4376},
  doi = {10.1109/IECON.2009.5414907},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77951582516&doi=10.1109%2fIECON.2009.5414907&partnerID=40&md5=87110eb411323e6be572de8c653e15ec},
  abstract = {Fierce global competition, rapid market changes and short product life cycles originated the diffusion of automated warehousing systems. This paper focuses on the performance evaluation and management of an Automated Distribution Center (ADC), i.e., a specific and automated type of warehouse where storage of products is limited or non-existent and the core activity is the sorting operation. We consider a case study in the clothing factory and we model the ADC as a discrete event system by way of the UML formalism, a graphic and textual modeling language intended to describe systems from structural and dynamics viewpoints. The ADC is simulated in the well-known ARENA simulation software environment under several scenarios, in which different system parameters are considered, e.g. number of material handling operators, speeds of machines, dimensions of pallets etc. The employed approach enables us to successfully select crucial parameters in order to improve the ADC management. ©2009 IEEE.},
  keywords = {Automation; Computer software; Industrial electronics; Materials handling; Warehouses; Arena simulations; Automated distribution; Core activity; Crucial parameters; Discrete event systems; Global competition; Market changes; Material handling; Modeling languages; Performance analysis; Performance evaluation; Short product; Warehousing systems; Multicarrier modulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

• Boschian, V., Dotoli, M., Fanti, M. P., Iacobellis, G. & Ukovich, W. (2009) A metamodelling approach to the management of intermodal transportation networks IN Intelligent Vehicle Controls and Intelligent Transportation Systems – Proceedings of the 3rd International Workshop – IVC and ITS 2009 In Conjunction with ICINCO 2009., 96 – 105.
  [BibTeX] [Abstract] [Download PDF]

  The paper develops a novel and broad metamodel of a generic Intermodal Transportation Network (ITN), devoted to provide a reference model for the real time management and control of such systems. In order to take operational decisions, the presented model describes in detail the ITN structure and dynamic evolution that is updated on the basis of the information obtained in real time by modern information and communication technologies tools. The proposed metamodelling approach consists in employing a top down procedure and is based on the UML formalism, a graphic and textual modelling language intended to describe systems from structural and dynamics viewpoints. Hence, the paper models a generic ITN starting from the network description and shows as an example the metamodel of one of the most important nodes that compose it: the port subsystem. To this aim, we present the main UML diagrams describing the structure and dynamics of a case study.

  @CONFERENCE{Boschian200996,
  author = {Boschian, Valentina and Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio and Ukovich, Walter},
  title = {A metamodelling approach to the management of intermodal transportation networks},
  year = {2009},
  journal = {Intelligent Vehicle Controls and Intelligent Transportation Systems - Proceedings of the 3rd International Workshop - IVC and ITS 2009 In Conjunction with ICINCO 2009},
  pages = {96 – 105},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-74549210097&partnerID=40&md5=e77aec3c0a65bdeaa4d9a12c18d92761},
  abstract = {The paper develops a novel and broad metamodel of a generic Intermodal Transportation Network (ITN), devoted to provide a reference model for the real time management and control of such systems. In order to take operational decisions, the presented model describes in detail the ITN structure and dynamic evolution that is updated on the basis of the information obtained in real time by modern information and communication technologies tools. The proposed metamodelling approach consists in employing a top down procedure and is based on the UML formalism, a graphic and textual modelling language intended to describe systems from structural and dynamics viewpoints. Hence, the paper models a generic ITN starting from the network description and shows as an example the metamodel of one of the most important nodes that compose it: the port subsystem. To this aim, we present the main UML diagrams describing the structure and dynamics of a case study.},
  keywords = {Control system synthesis; Intelligent vehicle highway systems; Real time systems; Transportation; Information and Communication Technologies; Meta model; Meta-modelling; Modelling language; Operational decisions; Paper models; Real time; Real-time management; Reference models; Structure and dynamics; Topdown; UML diagrams; Intermodal transportation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 2}
  }

• Dotoli, M., Fanti, M. P., Mangini, A. M. & Ukovich, W. (2009) On-line fault detection in discrete event systems by Petri nets and integer linear programming. IN Automatica, 45.2665 – 2672. doi:10.1016/j.automatica.2009.07.021
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the fault detection problem for discrete event systems in a Petri Net (PN) framework. Assuming that the structure of the PN model and the initial marking are known, faults are modelled by unobservable transitions. Moreover, we assume that there may be additional unobservable transitions associated with the system legal behaviour and that the marking reached after the firing of any transition is unknown. The proposed diagnoser works on-line: it waits for the firing of an observable transition and employs an algorithm based on the definition and solution of some integer linear programming problems to decide whether the system behaviour is normal or exhibits some possible faults. The results characterize the properties that the PN modelling the system fault behaviour has to fulfill in order to reduce the on-line computational effort. © 2009 Elsevier Ltd. All rights reserved.

  @ARTICLE{Dotoli20092665,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello and Ukovich, Walter},
  title = {On-line fault detection in discrete event systems by Petri nets and integer linear programming},
  year = {2009},
  journal = {Automatica},
  volume = {45},
  number = {11},
  pages = {2665 – 2672},
  doi = {10.1016/j.automatica.2009.07.021},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70349884020&doi=10.1016%2fj.automatica.2009.07.021&partnerID=40&md5=0cfc9d084d8efaae951a91dc8ea6cbbe},
  abstract = {The paper addresses the fault detection problem for discrete event systems in a Petri Net (PN) framework. Assuming that the structure of the PN model and the initial marking are known, faults are modelled by unobservable transitions. Moreover, we assume that there may be additional unobservable transitions associated with the system legal behaviour and that the marking reached after the firing of any transition is unknown. The proposed diagnoser works on-line: it waits for the firing of an observable transition and employs an algorithm based on the definition and solution of some integer linear programming problems to decide whether the system behaviour is normal or exhibits some possible faults. The results characterize the properties that the PN modelling the system fault behaviour has to fulfill in order to reduce the on-line computational effort. © 2009 Elsevier Ltd. All rights reserved.},
  author_keywords = {Discrete event systems; Fault detection; Integer programming; Petri nets},
  keywords = {Dynamic programming; Fault detection; Graph theory; Integer programming; Linearization; Petri nets; Computational effort; Discrete event systems; Fault detection problem; Initial marking; Integer Linear Programming; On-line fault detection; PN models; System faults; Unobservable; Mathematical models},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 147}
  }

• Dotoli, M., Fanti, M. P., Mangini, A. M. & Ukovich, W. (2009) A continuous Petri net model for the management and design of Emergency Cardiology Departments IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 50 – 55. doi:10.3182/20090916-3-es-3003.00010
  [BibTeX] [Abstract] [Download PDF]

  The efficient management of the Emergency Department (ED) has become an important issue in the past decade. Indeed, the increased demand for emergency services has saturated the capacity of EDs that require suitable tools for the efficient flow of work and people. The paper proposes a model to describe in a concise and effective way the structure and dynamics of a critical ED of the general hospital of Bari (Italy): the Emergency Cardiology Department (ECD). The model describes in a continuous Petri net framework the complete workflow and management of patients starting from their arrival to the ED until either their discharge from the hospital or their admission in a suitable hospital department. The fluid approximation allows defining suitable optimization problems to optimize the system performances and determine the optimal resource dimension guaranteeing the efficient management of the ECD. A simulation study shows that the optimized parameters lead to an effective workflow organization while maximizing the patient flow.

  @CONFERENCE{Dotoli200950,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino M. and Ukovich, Walter},
  title = {A continuous Petri net model for the management and design of Emergency Cardiology Departments},
  year = {2009},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {3},
  number = {PART 1},
  pages = {50 – 55},
  doi = {10.3182/20090916-3-es-3003.00010},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960969597&doi=10.3182%2f20090916-3-es-3003.00010&partnerID=40&md5=7f79c544ef40a4c444d0eed7d5e5b39c},
  abstract = {The efficient management of the Emergency Department (ED) has become an important issue in the past decade. Indeed, the increased demand for emergency services has saturated the capacity of EDs that require suitable tools for the efficient flow of work and people. The paper proposes a model to describe in a concise and effective way the structure and dynamics of a critical ED of the general hospital of Bari (Italy): the Emergency Cardiology Department (ECD). The model describes in a continuous Petri net framework the complete workflow and management of patients starting from their arrival to the ED until either their discharge from the hospital or their admission in a suitable hospital department. The fluid approximation allows defining suitable optimization problems to optimize the system performances and determine the optimal resource dimension guaranteeing the efficient management of the ECD. A simulation study shows that the optimized parameters lead to an effective workflow organization while maximizing the patient flow.},
  author_keywords = {Continuous Petri nets; Healthcare systems; Modeling; Performance evaluation; Simulation},
  keywords = {Cardiology; Emergency rooms; Hybrid systems; Models; Patient monitoring; Petri nets; Continuous Petri net; Efficient managements; Emergency departments; Health-care system; Optimization problems; Performance evaluation; Simulation; Structure and dynamics; Emergency services},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 18; All Open Access, Bronze Open Access}
  }

• Dotoli, M., Fanti, M. P., Mangini, A. M., Stecco, G. & Ukovich, W. (2009) The impact of ICT on an intermodal transportation system: An analysis by petri nets IN 2009 IEEE International Conference on Automation Science and Engineering, CASE 2009., 513 – 518. doi:10.1109/COASE.2009.5234159
  [BibTeX] [Abstract] [Download PDF]

  Intermodal Transportation Systems (ITS) are logistics networks integrating different transportation services, designed to move goods from origin to destination in a timely manner and using intermodal transportation means. This paper addresses the problem of the modeling and management of ITS at the operational level considering the impact that the new Information and Communication Technologies (ICT) tools can have on management and control of these systems. An effective ITS model at the operational level should focus on evaluating performance indices describing activities, resources and concurrency, by integrating information and financial flows. To this aim, ITS are regarded as discrete event systems and are modeled in a Petri net framework. We consider as a case study the ferry terminal of Trieste (Italy) that is described and simulated in different operative conditions characterized by different types of ICT solutions and information. The simulation results show that ICT have a huge potential for efficient real time management and operation of ITS, as well as an effective impact on the infrastructures. © 2009 IEEE.

  @CONFERENCE{Dotoli2009513,
  author = {Dotoli, Mariagrazia and Fanti, Maria P. and Mangini, Agostino M. and Stecco, Gabriella and Ukovich, Walter},
  title = {The impact of ICT on an intermodal transportation system: An analysis by petri nets},
  year = {2009},
  journal = {2009 IEEE International Conference on Automation Science and Engineering, CASE 2009},
  pages = {513 – 518},
  doi = {10.1109/COASE.2009.5234159},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70449090327&doi=10.1109%2fCOASE.2009.5234159&partnerID=40&md5=10e95b4890f14d377b053e1b43893764},
  abstract = {Intermodal Transportation Systems (ITS) are logistics networks integrating different transportation services, designed to move goods from origin to destination in a timely manner and using intermodal transportation means. This paper addresses the problem of the modeling and management of ITS at the operational level considering the impact that the new Information and Communication Technologies (ICT) tools can have on management and control of these systems. An effective ITS model at the operational level should focus on evaluating performance indices describing activities, resources and concurrency, by integrating information and financial flows. To this aim, ITS are regarded as discrete event systems and are modeled in a Petri net framework. We consider as a case study the ferry terminal of Trieste (Italy) that is described and simulated in different operative conditions characterized by different types of ICT solutions and information. The simulation results show that ICT have a huge potential for efficient real time management and operation of ITS, as well as an effective impact on the infrastructures. © 2009 IEEE.},
  keywords = {Graph theory; Information technology; Petri nets; Simulators; Transportation; Discrete event systems; Financial flows; Integrating information; Intermodal transportation; Logistics network; New information and communication technologies; Operational level; Performance indices; Real-time management; Simulation result; Transportation services; Trieste; Intelligent vehicle highway systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Dotoli, M., Fanti, M. P., Iacobellis, G. & Mangini, A. M. (2009) A first-order hybrid petri net model for supply chain management. IN IEEE Transactions on Automation Science and Engineering, 6.744 – 758. doi:10.1109/TASE.2009.2021362
  [BibTeX] [Abstract] [Download PDF]

  A supply chain (SC) is a network of independent manufacturing and logistics companies that perform the critical functions in the order fulfillment process. This paper proposes an effective and modular model to describe material, financial and information flow of SCs at the operational level based on first-order hybrid Petri nets (PNs), i.e., PNs that make use of first-order fluid approximation. The proposed formalism enables the SC designer to choose suitable production rates of facilities in order to optimize the chosen objective function. The optimal mode of operation is performed based on the state knowledge of the obtained linear discrete-time, time-varying state variable model in order to react to unpredictable events such as the blocking of a supply or an accident in a transportation facility. A case study is modeled in the proposed framework and is simulated under three different closed-loop control strategies. © 2006 IEEE.

  @ARTICLE{Dotoli2009744,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio and Mangini, Agostino Marcello},
  title = {A first-order hybrid petri net model for supply chain management},
  year = {2009},
  journal = {IEEE Transactions on Automation Science and Engineering},
  volume = {6},
  number = {4},
  pages = {744 – 758},
  doi = {10.1109/TASE.2009.2021362},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70350035689&doi=10.1109%2fTASE.2009.2021362&partnerID=40&md5=66a2991f2030fe1aa6071a5181fb567d},
  abstract = {A supply chain (SC) is a network of independent manufacturing and logistics companies that perform the critical functions in the order fulfillment process. This paper proposes an effective and modular model to describe material, financial and information flow of SCs at the operational level based on first-order hybrid Petri nets (PNs), i.e., PNs that make use of first-order fluid approximation. The proposed formalism enables the SC designer to choose suitable production rates of facilities in order to optimize the chosen objective function. The optimal mode of operation is performed based on the state knowledge of the obtained linear discrete-time, time-varying state variable model in order to react to unpredictable events such as the blocking of a supply or an accident in a transportation facility. A case study is modeled in the proposed framework and is simulated under three different closed-loop control strategies. © 2006 IEEE.},
  author_keywords = {Management; Modeling; Performance evaluation; Petri nets (PNs); Simulation; Supply chains (SCs)},
  keywords = {Bottling plants; Closed loop control systems; Graph theory; Petri nets; Simulators; Supply chain management; Closed-loop control; Critical functions; Discrete-time; First-order; First-order hybrid Petri nets; Fluid approximation; Hybrid Petri net; Information flows; Logistics company; Modeling; Objective functions; Operational level; Optimal modes; Order fulfillment process; Performance evaluation; Production rates; Simulation; State-variable model; Time varying; Transportation facilities; Supply chains},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 55}
  }

• Dotoli, M., Fanti, M. P., Mangini, A. M. & Ukovich, W. (2009) Identification of DES unobservable behaviour by Petri Nets IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 99 – 104. doi:10.3182/20090610-3-it-4004.00022
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the problem of the on-line identification of Petri Nets (PN) modelling the unobservable behaviour of Discrete Event Systems (DES). Starting from a previous specification of an identifier that monitors the DES events and the corresponding available place markings, the paper proves some results that make the on-line identification of reasonable complexity. Assuming that the PN system modelling the observable events is known, at each event occurrence an identification algorithm recursively updates and provides as an output the complete PN system describing both the observable and unobservable DES behaviour. An example shows an application of the proposed technique. © 2009 IFAC.

  @CONFERENCE{Dotoli200999,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino M. and Ukovich, Walter},
  title = {Identification of DES unobservable behaviour by Petri Nets},
  year = {2009},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {2},
  number = {PART 1},
  pages = {99 – 104},
  doi = {10.3182/20090610-3-it-4004.00022},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960955648&doi=10.3182%2f20090610-3-it-4004.00022&partnerID=40&md5=1d26ab825b3bccc1e6559170dec1a9c8},
  abstract = {The paper addresses the problem of the on-line identification of Petri Nets (PN) modelling the unobservable behaviour of Discrete Event Systems (DES). Starting from a previous specification of an identifier that monitors the DES events and the corresponding available place markings, the paper proves some results that make the on-line identification of reasonable complexity. Assuming that the PN system modelling the observable events is known, at each event occurrence an identification algorithm recursively updates and provides as an output the complete PN system describing both the observable and unobservable DES behaviour. An example shows an application of the proposed technique. © 2009 IFAC.},
  author_keywords = {Discrete Event Systems; Identification algorithms; Integer programming; Modelling; Petri Nets},
  keywords = {Integer programming; Models; Petri nets; Identification algorithms; On-line identification; System modelling; Unobservable; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1; All Open Access, Bronze Open Access}
  }

• Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P. & Iacobellis, G. (2009) A decision support system framework for purchasing management in supply chains. IN Journal of Business and Industrial Marketing, 24.278 – 290. doi:10.1108/08858620910939822
  [BibTeX] [Abstract] [Download PDF]

  Purpose: This paper aims to propose the framework of a decision support system (DSS) to select the optimal number of suppliers that are candidate to join a supply chain network. Design/methodology/approach: The DSS bases the decision on the cost evaluation of the transaction among the buyer and the potentially available suppliers by way of a Monte Carlo approach. In particular, the presented DSS includes a statistical module and the DSS core. The former module estimates (in a probabilistic way) the exchange performance indices, i.e. total cost of the transaction, purchasing price and additional costs of purchasing, while the latter module implements the transaction evolution making use of a simulation model. The DSS is tested by way of a case study, namely the supply of a customized product by a general contractor in the construction industry. Findings: The obtained DSS results are validated with the actual data of the purchasing, and confirm the underlying model suitability and the DSS effectiveness for purchasing management in supply chains. The DSS is able to evaluate the total cost of purchasing and the optimal number of suppliers to contact before the transaction takes place and may be employed by the buyer to forecast the cost of the purchase and take decisions to minimize such a performance index of the exchange. Research limitations/implications: Perspectives on future research include further validations of the DSS, also considering other factors than price in the transaction evaluation. Originality/value: The paper shows that the DSS can be successfully employed to identify managerial guidelines that can be followed by practitioners, particularly when the first supply of a product has to be carried out. © Emerald Group Publishing Limited.

  @ARTICLE{Costantino2009278,
  author = {Costantino, Nicola and Dotoli, Mariagrazia and Falagario, Marco and Fanti, Maria Pia and Iacobellis, Giorgio},
  title = {A decision support system framework for purchasing management in supply chains},
  year = {2009},
  journal = {Journal of Business and Industrial Marketing},
  volume = {24},
  number = {3-4},
  pages = {278 – 290},
  doi = {10.1108/08858620910939822},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-69449100683&doi=10.1108%2f08858620910939822&partnerID=40&md5=0bc27b827bd9da31ca2fcf387b647907},
  abstract = {Purpose: This paper aims to propose the framework of a decision support system (DSS) to select the optimal number of suppliers that are candidate to join a supply chain network. Design/methodology/approach: The DSS bases the decision on the cost evaluation of the transaction among the buyer and the potentially available suppliers by way of a Monte Carlo approach. In particular, the presented DSS includes a statistical module and the DSS core. The former module estimates (in a probabilistic way) the exchange performance indices, i.e. total cost of the transaction, purchasing price and additional costs of purchasing, while the latter module implements the transaction evolution making use of a simulation model. The DSS is tested by way of a case study, namely the supply of a customized product by a general contractor in the construction industry. Findings: The obtained DSS results are validated with the actual data of the purchasing, and confirm the underlying model suitability and the DSS effectiveness for purchasing management in supply chains. The DSS is able to evaluate the total cost of purchasing and the optimal number of suppliers to contact before the transaction takes place and may be employed by the buyer to forecast the cost of the purchase and take decisions to minimize such a performance index of the exchange. Research limitations/implications: Perspectives on future research include further validations of the DSS, also considering other factors than price in the transaction evaluation. Originality/value: The paper shows that the DSS can be successfully employed to identify managerial guidelines that can be followed by practitioners, particularly when the first supply of a product has to be carried out. © Emerald Group Publishing Limited.},
  author_keywords = {Decision support systems; Monte Carlo methods; Purchasing; Supply chain management; Transaction costs},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 16}
  }

2008

• Dotoli, M., Fanti, M. P., Mangini, A. M. & Ukovich, W. (2008) A model to describe the hospital drug distribution system via first order hybrid Petri nets IN 20th European Modeling and Simulation Symposium, EMSS 2008., 700 – 705.
  [BibTeX] [Abstract] [Download PDF]

  The paper proposes a model for simulation and performance evaluation of the hospital drug distribution system, a key process for the effectiveness and efficiency of the hospital offered services. In particular, we propose a modeling technique employing the first order hybrid Petri nets formalism, i.e., Petri nets making use of first order fluid approximation. The presented model is able to effectively describe the typical doctors and nurses daily operations and may be employed for staffing performance evaluation and optimization. A simulation of the drug distribution system of a department of an Italian hospital is performed in the well-known MATLAB environment to enlighten the potential of the proposed model.

  @CONFERENCE{Dotoli2008700,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello and Ukovich, Walter},
  title = {A model to describe the hospital drug distribution system via first order hybrid Petri nets},
  year = {2008},
  journal = {20th European Modeling and Simulation Symposium, EMSS 2008},
  pages = {700 – 705},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871541608&partnerID=40&md5=d912595050141ec47be7f4f8f8633154},
  abstract = {The paper proposes a model for simulation and performance evaluation of the hospital drug distribution system, a key process for the effectiveness and efficiency of the hospital offered services. In particular, we propose a modeling technique employing the first order hybrid Petri nets formalism, i.e., Petri nets making use of first order fluid approximation. The presented model is able to effectively describe the typical doctors and nurses daily operations and may be employed for staffing performance evaluation and optimization. A simulation of the drug distribution system of a department of an Italian hospital is performed in the well-known MATLAB environment to enlighten the potential of the proposed model.},
  author_keywords = {Hospital drug distribution system; Hybrid Petri nets; Modeling; Performance evaluation},
  keywords = {Hospitals; MATLAB; Models; Petri nets; Drug distribution; First order; First-order hybrid Petri nets; Fluid approximation; Hybrid Petri net; Key process; MATLAB environment; Modeling technique; Performance evaluation; Via first; Computer simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2008) Real time identification of discrete event systems using Petri nets. IN Automatica, 44.1209 – 1219. doi:10.1016/j.automatica.2007.10.014
  [BibTeX] [Abstract] [Download PDF]

  The paper defines the identification problem for Discrete Event Systems (DES) as the problem of inferring a Petri Net (PN) model using the observation of the events and the available output vectors, that correspond to the markings of the measurable places. Two cases are studied considering different levels of the system knowledge. In the first case the place and transition sets are assumed known. Hence, an integer linear programming problem is defined in order to determine a PN modelling the DES. In the second case the transition and place sets are assumed unknown and only an upper bound of the number of places is given. Hence, the identification problem is solved by an identification algorithm that observes in real time the occurred events and the corresponding output vectors. The integer linear programming problem is defined at each observation so that the PN can be recursively identified. Some results and examples characterize the identified PN systems and show the flexibility and simplicity of the proposed technique. Moreover, an application to the synthesis of supervisory control of PN systems via monitor places is proposed. © 2008 Elsevier Ltd. All rights reserved.

  @ARTICLE{Dotoli20081209,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello},
  title = {Real time identification of discrete event systems using Petri nets},
  year = {2008},
  journal = {Automatica},
  volume = {44},
  number = {5},
  pages = {1209 – 1219},
  doi = {10.1016/j.automatica.2007.10.014},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-41949092080&doi=10.1016%2fj.automatica.2007.10.014&partnerID=40&md5=12361e79dc1653207df3c46c549a1f58},
  abstract = {The paper defines the identification problem for Discrete Event Systems (DES) as the problem of inferring a Petri Net (PN) model using the observation of the events and the available output vectors, that correspond to the markings of the measurable places. Two cases are studied considering different levels of the system knowledge. In the first case the place and transition sets are assumed known. Hence, an integer linear programming problem is defined in order to determine a PN modelling the DES. In the second case the transition and place sets are assumed unknown and only an upper bound of the number of places is given. Hence, the identification problem is solved by an identification algorithm that observes in real time the occurred events and the corresponding output vectors. The integer linear programming problem is defined at each observation so that the PN can be recursively identified. Some results and examples characterize the identified PN systems and show the flexibility and simplicity of the proposed technique. Moreover, an application to the synthesis of supervisory control of PN systems via monitor places is proposed. © 2008 Elsevier Ltd. All rights reserved.},
  author_keywords = {Discrete event systems; Identification algorithms; Integer programming; Petri nets},
  keywords = {Identification (control systems); Integer programming; Linear programming; Petri nets; Real time systems; Identification algorithms; Real time identification; Discrete event simulation},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 66}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2008) Fault monitoring of automated manufacturing systems by first order hybrid petri nets IN 4th IEEE Conference on Automation Science and Engineering, CASE 2008., 181 – 186. doi:10.1109/COASE.2008.4626493
  [BibTeX] [Abstract] [Download PDF]

  Fault monitoring plays an important role for safety and reliability of industrial systems. We present a novel on-line monitoring technique for automated manufacturing systems employing the first order hybrid Petri nets formalism, i.e., Petri nets making use of first order fluid approximation. The proposed fault analysis approach belongs to the class of event based methodologies, so that the state space explosion problem is avoided. Moreover, the presented technique relies on a modular framework: elementary monitors can be connected with other monitors to check complex systems. Timely and accurate detection of system failures is ensured, i.e., faults are detected before the maximum execution time assigned to each task. An application to an automated manufacturing system proposed in the related literature enlightens the simplicity and modularity of the technique. ©2008 IEEE.

  @CONFERENCE{Dotoli2008181,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino M.},
  title = {Fault monitoring of automated manufacturing systems by first order hybrid petri nets},
  year = {2008},
  journal = {4th IEEE Conference on Automation Science and Engineering, CASE 2008},
  pages = {181 – 186},
  doi = {10.1109/COASE.2008.4626493},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-54949141198&doi=10.1109%2fCOASE.2008.4626493&partnerID=40&md5=82f63861faeb83399b65e0dadecf02f2},
  abstract = {Fault monitoring plays an important role for safety and reliability of industrial systems. We present a novel on-line monitoring technique for automated manufacturing systems employing the first order hybrid Petri nets formalism, i.e., Petri nets making use of first order fluid approximation. The proposed fault analysis approach belongs to the class of event based methodologies, so that the state space explosion problem is avoided. Moreover, the presented technique relies on a modular framework: elementary monitors can be connected with other monitors to check complex systems. Timely and accurate detection of system failures is ensured, i.e., faults are detected before the maximum execution time assigned to each task. An application to an automated manufacturing system proposed in the related literature enlightens the simplicity and modularity of the technique. ©2008 IEEE.},
  keywords = {Dense wavelength division multiplexing; Graph theory; Marine biology; Petri nets; Production engineering; Safety engineering; State space methods; Systems engineering; Accurate; Automated manufacturing systems; Complex systems; Event based; Execution times; Fault analyses; Fault monitoring; First-order; Fluid approximations; Hybrid Petri nets; Industrial systems; Modular frameworks; Modularity; On-line; State spaces; System failures; Automation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Dotoli, M., Fanti, M. P. & Iacobellis, G. (2008) An urban traffic network model by first order hybrid petri nets IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 1929 – 1934. doi:10.1109/ICSMC.2008.4811572
  [BibTeX] [Abstract] [Download PDF]

  The paper proposes a model for real time control of urban traffic networks. A modular framework based on first order hybrid Petri nets models the vehicle flows by a first order fluid approximation. Moreover, the lane interruptions and the signal timing plan controlling the area are described by the discrete event dynamics using timed Petri nets. The proposed model is applied to a real intersection located in Bari, Italy. Simulation of different scenarios shows the technique efficiency: validation is performed by comparison with a previously proposed alternative approach employing colored Petri nets. © 2008 IEEE.

  @CONFERENCE{Dotoli20081929,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio},
  title = {An urban traffic network model by first order hybrid petri nets},
  year = {2008},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  pages = {1929 – 1934},
  doi = {10.1109/ICSMC.2008.4811572},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-69949182421&doi=10.1109%2fICSMC.2008.4811572&partnerID=40&md5=7ad40a1738fa0a6b4f14907d824d687b},
  abstract = {The paper proposes a model for real time control of urban traffic networks. A modular framework based on first order hybrid Petri nets models the vehicle flows by a first order fluid approximation. Moreover, the lane interruptions and the signal timing plan controlling the area are described by the discrete event dynamics using timed Petri nets. The proposed model is applied to a real intersection located in Bari, Italy. Simulation of different scenarios shows the technique efficiency: validation is performed by comparison with a previously proposed alternative approach employing colored Petri nets. © 2008 IEEE.},
  author_keywords = {Hybrid Petri nets; Modeling; Simulation; Urban traffic control},
  keywords = {Control theory; Cybernetics; Graph theory; Petri nets; Real time control; Traffic control; Alternative approach; Colored Petri Nets; Discrete event dynamics; First order; First-order hybrid Petri nets; Fluid approximation; Hybrid Petri nets; Modeling; Modular framework; Signal timing plan; Simulation; Timed Petri Net; Urban traffic control; Urban traffic networks; Vehicle flow; Simulators},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 24}
  }

• Fanti, M. P., Dotoli, M. & Mangini, A. M. (2008) Fault detection of discrete event systems using Petri nets and integer linear programming IN IFAC Proceedings Volumes (IFAC-PapersOnline).. doi:10.3182/20080706-5-KR-1001.1414
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the fault detection problem for discrete event systems on the basis of a Petri Net (PN) model. Assuming that the structure of the PN and the initial marking are known, faults are modelled by unobservable transitions. Moreover, we assume that there may be additional unobservable transitions that are associated with the system legal behaviour and that the marking reached after the firing of a transition is unknown. We propose a diagnoser that works on-line: it waits for the firing of an observable transition and employs an algorithm based on the definition of some integer linear programming problems to decide whether the system behaviour is normal or exhibits some possible faults. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.

  @CONFERENCE{Fanti2008,
  author = {Fanti, Maria Pia and Dotoli, Mariagrazia and Mangini, Agostino Marcello},
  title = {Fault detection of discrete event systems using Petri nets and integer linear programming},
  year = {2008},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {17},
  number = {1 PART 1},
  doi = {10.3182/20080706-5-KR-1001.1414},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79961020315&doi=10.3182%2f20080706-5-KR-1001.1414&partnerID=40&md5=f98d947726f39837999e3837999c4f6d},
  abstract = {The paper addresses the fault detection problem for discrete event systems on the basis of a Petri Net (PN) model. Assuming that the structure of the PN and the initial marking are known, faults are modelled by unobservable transitions. Moreover, we assume that there may be additional unobservable transitions that are associated with the system legal behaviour and that the marking reached after the firing of a transition is unknown. We propose a diagnoser that works on-line: it waits for the firing of an observable transition and employs an algorithm based on the definition of some integer linear programming problems to decide whether the system behaviour is normal or exhibits some possible faults. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.},
  author_keywords = {Automata, Petri nets and other tools; Discrete event systems modeling and control; Fault detection and diagnosis},
  keywords = {Automata theory; Dynamic programming; Graph theory; Integer programming; Linearization; Petri nets; Translation (languages); Automata, Petri nets and other tools; Discrete event systems; Discrete event systems modeling and control; Fault detection and diagnosis; Fault detection problem; Initial marking; Integer Linear Programming; Petri net models; Unobservable; Fault detection},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 16}
  }

• Dotoli, M., Fanti, M. P., Mangini, A. M. & Ukovich, W. (2008) Modelling and design of hospital departments by timed continuous petri nets IN 7th International Workshop on Modeling and Applied Simulation, MAS 2008, Held at the International Mediterranean Modeling Multiconference, I3M 2008., 175 – 180.
  [BibTeX] [Abstract] [Download PDF]

  This paper proposes a model to describe in a concise and detailed way the flow of patients in a hospital starting from their arrival to the emergency medical service to the assignment of beds in the suitable department and finally the discharge. The model is based on a continuous Petri nets framework, whose fluid approximation allows us to define suitable optimization problems in order to plan the system capacity, e.g., determining the medical and nursing staff dimension and the number of beds. A case study and a simulation and optimization analysis show the efficiency of the model.

  @CONFERENCE{Dotoli2008175,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello and Ukovich, Walter},
  title = {Modelling and design of hospital departments by timed continuous petri nets},
  year = {2008},
  journal = {7th International Workshop on Modeling and Applied Simulation, MAS 2008, Held at the International Mediterranean Modeling Multiconference, I3M 2008},
  pages = {175 – 180},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898779266&partnerID=40&md5=8d24cb7b150b264b18ece389443ce397},
  abstract = {This paper proposes a model to describe in a concise and detailed way the flow of patients in a hospital starting from their arrival to the emergency medical service to the assignment of beds in the suitable department and finally the discharge. The model is based on a continuous Petri nets framework, whose fluid approximation allows us to define suitable optimization problems in order to plan the system capacity, e.g., determining the medical and nursing staff dimension and the number of beds. A case study and a simulation and optimization analysis show the efficiency of the model.},
  author_keywords = {Continuous Petri nets; Hospital department; Modeling; Performance evaluation},
  keywords = {Hospitals; Medical problems; Models; Optimization; Petri nets; Continuous Petri net; Emergency medical services; Fluid approximation; Optimization problems; Performance evaluation; Simulation and optimization; System Capacity; Timed continuous petri nets; Computer simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M., Fanti, M. P., Mangini, A. M. & Ukovich, W. (2008) On-line identification of petri nets with unobservable transitions IN Proceedings – 9th International Workshop on Discrete Event Systems, WODES’ 08., 449 – 454. doi:10.1109/WODES.2008.4605988
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the problem of the on-line identification of Petri Nets (PNs) modeling Discrete Event Systems (DESs) that exhibit unobservable events. The identifier monitors the DES events and the corresponding available place markings. Assuming that the observable transition set, the place set and the corresponding PN structure are known, at each event occurrence an identification algorithm defines and solves some integer linear programming problems. We prove that the complete PN system describing both the observable and unobservable DES behavior is recursively identified. An example shows an application of the proposed technique. ©2008 IEEE.

  @CONFERENCE{Dotoli2008449,
  author = {Dotoli, M. and Fanti, M.P. and Mangini, A.M. and Ukovich, W.},
  title = {On-line identification of petri nets with unobservable transitions},
  year = {2008},
  journal = {Proceedings - 9th International Workshop on Discrete Event Systems, WODES' 08},
  pages = {449 – 454},
  doi = {10.1109/WODES.2008.4605988},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-53149095035&doi=10.1109%2fWODES.2008.4605988&partnerID=40&md5=3c6d68ca1745aec9a6cdf2cd007eed2d},
  abstract = {The paper addresses the problem of the on-line identification of Petri Nets (PNs) modeling Discrete Event Systems (DESs) that exhibit unobservable events. The identifier monitors the DES events and the corresponding available place markings. Assuming that the observable transition set, the place set and the corresponding PN structure are known, at each event occurrence an identification algorithm defines and solves some integer linear programming problems. We prove that the complete PN system describing both the observable and unobservable DES behavior is recursively identified. An example shows an application of the proposed technique. ©2008 IEEE.},
  keywords = {Graph theory; Integer programming; Linearization; Marine biology; Petri nets; Technical presentations; Discrete event systems; Identification algorithms; Integer linear programming problems; On-line identification; Paper addresses; Unobservable; Linear programming},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Dotoli, M., Fanti, M. P., Giua, A. & Seatzu, C. (2008) First-order hybrid Petri nets. An application to distributed manufacturing systems. IN Nonlinear Analysis: Hybrid Systems, 2.408 – 430. doi:10.1016/j.nahs.2006.05.005
  [BibTeX] [Abstract] [Download PDF]

  In this paper we consider Hybrid Petri Nets (HPNs), a particular formalism that combines fluid and discrete event dynamics. We first provide a survey of the main HPN models that have been presented in the literature in the last decades. Then, we focus on a particular HPN model, namely the First-Order Hybrid Petri Net (FOHPN) model, whose continuous dynamics are piece-wise constant. Here the problem of designing an optimal controller simply requires solving on-line an appropriate linear integer programming problem. In this paper we show how FOHPNs can efficiently represent the concurrent activities of Distributed Manufacturing Systems (DMS), and some interesting optimization problems are also solved via numerical simulation. © 2007 Elsevier Ltd. All rights reserved.

  @ARTICLE{Dotoli2008408,
  author = {Dotoli, M. and Fanti, M.P. and Giua, A. and Seatzu, C.},
  title = {First-order hybrid Petri nets. An application to distributed manufacturing systems},
  year = {2008},
  journal = {Nonlinear Analysis: Hybrid Systems},
  volume = {2},
  number = {2},
  pages = {408 – 430},
  doi = {10.1016/j.nahs.2006.05.005},
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  abstract = {In this paper we consider Hybrid Petri Nets (HPNs), a particular formalism that combines fluid and discrete event dynamics. We first provide a survey of the main HPN models that have been presented in the literature in the last decades. Then, we focus on a particular HPN model, namely the First-Order Hybrid Petri Net (FOHPN) model, whose continuous dynamics are piece-wise constant. Here the problem of designing an optimal controller simply requires solving on-line an appropriate linear integer programming problem. In this paper we show how FOHPNs can efficiently represent the concurrent activities of Distributed Manufacturing Systems (DMS), and some interesting optimization problems are also solved via numerical simulation. © 2007 Elsevier Ltd. All rights reserved.},
  author_keywords = {Distributed manufacturing systems; First-order hybrid Petri nets; Hybrid Petri nets; Manufacturing systems},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 57}
  }

2007

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2007) Fuzzy multi-objective optimization for network design of integrated e-supply chains. IN International Journal of Computer Integrated Manufacturing, 20.588 – 601. doi:10.1080/09511920601079397
  [BibTeX] [Abstract] [Download PDF]

  Worldwide competition originated the development of integrated e-supply chains (IESC) that are distributed manufacturing systems integrating international logistics and information technologies with production. This work builds upon an IESC network design methodology previously proposed to select partners in the different IESC stages and the links connecting them. In order to rank the Pareto optimal solutions obtained by such a method, the paper proposes a second level IESC optimization performed using fuzzy logic. Indeed, fuzzy multi-criteria optimization is particularly suitable for choosing, on the basis of the subjective and qualitative knowledge provided by the decision makers, the IESC configuration from the set of Pareto optimal alternatives. Two fuzzification techniques and two different multi-criteria methods are considered. Moreover, a discussion on the different advantages and limitations of the proposed techniques is provided. Finally, the effectiveness of the methodology is illustrated by way of a case study.

  @ARTICLE{Dotoli2007588,
  author = {Dotoli, M. and Fanti, M.P. and Mangini, A.M.},
  title = {Fuzzy multi-objective optimization for network design of integrated e-supply chains},
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  journal = {International Journal of Computer Integrated Manufacturing},
  volume = {20},
  number = {6},
  pages = {588 – 601},
  doi = {10.1080/09511920601079397},
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  abstract = {Worldwide competition originated the development of integrated e-supply chains (IESC) that are distributed manufacturing systems integrating international logistics and information technologies with production. This work builds upon an IESC network design methodology previously proposed to select partners in the different IESC stages and the links connecting them. In order to rank the Pareto optimal solutions obtained by such a method, the paper proposes a second level IESC optimization performed using fuzzy logic. Indeed, fuzzy multi-criteria optimization is particularly suitable for choosing, on the basis of the subjective and qualitative knowledge provided by the decision makers, the IESC configuration from the set of Pareto optimal alternatives. Two fuzzification techniques and two different multi-criteria methods are considered. Moreover, a discussion on the different advantages and limitations of the proposed techniques is provided. Finally, the effectiveness of the methodology is illustrated by way of a case study.},
  author_keywords = {Fuzzy logic; Integrated e-supply chains; Network design; Optimization; Performance indices},
  keywords = {Decision making; Electronic commerce; Fuzzy logic; Integrated control; Multiobjective optimization; Fuzzification techniques; Integrated e-supply chains; Network design; Performance indices; Supply chain management},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2007) On line identification of discrete event systems via Petri nets: An application to monitor specification IN Proceedings of the 3rd IEEE International Conference on Automation Science and Engineering, IEEE CASE 2007., 893 – 898. doi:10.1109/COASE.2007.4341704
  [BibTeX] [Abstract] [Download PDF]

  The paper proves some properties of a previously proposed identification algorithm that builds on line the Petri net model of Discrete Event Systems (DES). The procedure uses the real time observation of the DES events and the corresponding available output vectors that partially provide the place markings. The paper shows how the considered identification method allows us to define a supervisory controller via monitor places enforcing generalized mutual exclusion constraints. To show the efficiency of the proposed approach, a communication gateway case study is presented. © 2007 IEEE.

  @CONFERENCE{Dotoli2007893,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino M.},
  title = {On line identification of discrete event systems via Petri nets: An application to monitor specification},
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  journal = {Proceedings of the 3rd IEEE International Conference on Automation Science and Engineering, IEEE CASE 2007},
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  abstract = {The paper proves some properties of a previously proposed identification algorithm that builds on line the Petri net model of Discrete Event Systems (DES). The procedure uses the real time observation of the DES events and the corresponding available output vectors that partially provide the place markings. The paper shows how the considered identification method allows us to define a supervisory controller via monitor places enforcing generalized mutual exclusion constraints. To show the efficiency of the proposed approach, a communication gateway case study is presented. © 2007 IEEE.},
  keywords = {Algorithms; Discrete event simulation; Petri nets; Real time systems; Exclusion constraints; Monitor specification; Identification (control systems)},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 5}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2007) Real time identification of discrete event systems by Petri Nets IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 241 – 246. doi:10.3182/20070613-3-fr-4909.00043
  [BibTeX] [Abstract] [Download PDF]

  The paper defines the identification problem for discrete event systems as the problem of inferring a Petri Net (PN) model using the observation of the events and the available output vectors. The transition and place sets are assumed unknown and only an upper bound of the number of places is given. Hence, the identification problem is solved by an algorithm that stores in real-time the occurred events and the corresponding output vectors. An integer linear programming problem is defined and solved at each observation so that the PN system can be recursively identified. An example shows the flexibility and simplicity of the proposed technique. Copyright © 2007 IFAC.

  @CONFERENCE{Dotoli2007241,
  author = {Dotoli, M. and Fanti, M.P. and Mangini, A.M.},
  title = {Real time identification of discrete event systems by Petri Nets},
  year = {2007},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {1},
  number = {PART 1},
  pages = {241 – 246},
  doi = {10.3182/20070613-3-fr-4909.00043},
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  abstract = {The paper defines the identification problem for discrete event systems as the problem of inferring a Petri Net (PN) model using the observation of the events and the available output vectors. The transition and place sets are assumed unknown and only an upper bound of the number of places is given. Hence, the identification problem is solved by an algorithm that stores in real-time the occurred events and the corresponding output vectors. An integer linear programming problem is defined and solved at each observation so that the PN system can be recursively identified. An example shows the flexibility and simplicity of the proposed technique. Copyright © 2007 IFAC.},
  author_keywords = {Discrete event systems; Identification; Integer linear programming; Petri nets},
  keywords = {Identification (control systems); Integer programming; Petri nets; Real time systems; Identification problem; Integer Linear Programming; Output vectors; Petri net models; Real time; Real-time identification; Upper Bound; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 5}
  }

• Dotoli, M. & Fanti, M. P. (2007) Deadlock detection and avoidance strategies for automated storage and retrieval systems. IN IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 37.541 – 552. doi:10.1109/TSMCC.2007.897690
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on real-time control of automated storage and retrieval systems (AS/RSs) serviced by a rail-guided vehicle system, a widely used solution for material handling in warehouses. The generic multiproduct AS/RS is modeled as a timed discrete event dynamical system, whose state provides the information on the current interactions between users and resources. Moreover, we address the real-time controller that governs resource allocations and scheduling choices by enabling and inhibiting the system events in order to avoid collisions and deadlocks. To this aim, we characterize deadlock in AS/RSs and define two deadlock resolution strategies: a deadlock avoidance and a deadlock detection/recovery policy. The proposed deadlock formulation and characterization have a general validity and can be applied to single unit resource allocation systems where a subset of users may be regarded as resources of other users. We compare the proposed control policies for a large-scale AS/RS presented in the related literature by several discrete event simulation tests. © 2007 IEEE.

  @ARTICLE{Dotoli2007541,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia},
  title = {Deadlock detection and avoidance strategies for automated storage and retrieval systems},
  year = {2007},
  journal = {IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews},
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  number = {4},
  pages = {541 – 552},
  doi = {10.1109/TSMCC.2007.897690},
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  abstract = {This paper focuses on real-time control of automated storage and retrieval systems (AS/RSs) serviced by a rail-guided vehicle system, a widely used solution for material handling in warehouses. The generic multiproduct AS/RS is modeled as a timed discrete event dynamical system, whose state provides the information on the current interactions between users and resources. Moreover, we address the real-time controller that governs resource allocations and scheduling choices by enabling and inhibiting the system events in order to avoid collisions and deadlocks. To this aim, we characterize deadlock in AS/RSs and define two deadlock resolution strategies: a deadlock avoidance and a deadlock detection/recovery policy. The proposed deadlock formulation and characterization have a general validity and can be applied to single unit resource allocation systems where a subset of users may be regarded as resources of other users. We compare the proposed control policies for a large-scale AS/RS presented in the related literature by several discrete event simulation tests. © 2007 IEEE.},
  author_keywords = {Automated storage and retrieval systems (AS/RSs); Deadlock avoidance (DA); Deadlock detection/recovery (DDR); Discrete event simulation; Real-time control},
  keywords = {Automatic train control; Collision avoidance; Discrete event simulation; Materials handling; Automated storage and retrieval system; Deadlock avoidance; Deadlock detection; Real time control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 28}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2007) Comparing management policies for supply chains via a hybrid petri net model IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 3469 – 3474. doi:10.1109/ICSMC.2007.4413684
  [BibTeX] [Abstract] [Download PDF]

  This paper presents a Supply Chain (SC) model at the operational level based on first order hybrid Petri Nets (PNs), i.e., PNs that make use of first order fluid approximation. The model addresses the issue of the management strategies that control the material flow and the inventory stocks in the SC. In particular, we apply the standard Make-To-Stock and Make-To-Order policies to a SC case study. Suitable inventory control rules manage the logistics, while optimal production rates are chosen according to a given objective function. © 2007 IEEE.

  @CONFERENCE{Dotoli20073469,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino M.},
  title = {Comparing management policies for supply chains via a hybrid petri net model},
  year = {2007},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  pages = {3469 – 3474},
  doi = {10.1109/ICSMC.2007.4413684},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-40949162283&doi=10.1109%2fICSMC.2007.4413684&partnerID=40&md5=288871ff4268a3cf4d9bcd8835591416},
  abstract = {This paper presents a Supply Chain (SC) model at the operational level based on first order hybrid Petri Nets (PNs), i.e., PNs that make use of first order fluid approximation. The model addresses the issue of the management strategies that control the material flow and the inventory stocks in the SC. In particular, we apply the standard Make-To-Stock and Make-To-Order policies to a SC case study. Suitable inventory control rules manage the logistics, while optimal production rates are chosen according to a given objective function. © 2007 IEEE.},
  keywords = {Inventory control; Mathematical models; Optimal control systems; Petri nets; Supply chains; Inventory stocks; Management strategies; Optimal production; Petri net models; Production control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

2006

• Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P. & Iacobellis, G. (2006) A petri net based decision support system for purchasing management in supply chains IN IFAC Proceedings Volumes (IFAC-PapersOnline)..
  [BibTeX] [Abstract] [Download PDF]

  The paper proposes a Decision Support System (DSS) to address the strategic issue of purchasing management in supply chains based on a transaction cost and purchasing price model employing probabilistic tools. The DSS is implemented in a novel high level Petri nets formalism, called Flow Coloured Petri Nets (FCPN). Several simulation tests of the FCPN model of the proposed DSS demonstrate the ability of the DSS in helping the buyer to determine the optimal number and the type of suppliers to involve in a transaction for a new product or service. Copyright © 2006 IFAC.

  @CONFERENCE{Costantino2006,
  author = {Costantino, N. and Dotoli, M. and Falagario, M. and Fanti, M.P. and Iacobellis, G.},
  title = {A petri net based decision support system for purchasing management in supply chains},
  year = {2006},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {12},
  number = {PART 1},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79961203263&partnerID=40&md5=1e43d3f78bd0494d268764499e2aae1f},
  abstract = {The paper proposes a Decision Support System (DSS) to address the strategic issue of purchasing management in supply chains based on a transaction cost and purchasing price model employing probabilistic tools. The DSS is implemented in a novel high level Petri nets formalism, called Flow Coloured Petri Nets (FCPN). Several simulation tests of the FCPN model of the proposed DSS demonstrate the ability of the DSS in helping the buyer to determine the optimal number and the type of suppliers to involve in a transaction for a new product or service. Copyright © 2006 IFAC.},
  author_keywords = {Decision support systems; Enterprise integration; Management systems; Petri-nets; Simulation},
  keywords = {Artificial intelligence; Computer simulation; Decision support systems; Information management; Manufacture; Petri nets; Sales; Supply chain management; Supply chains; Coloured Petri Nets; Enterprise Integration; High-level Petri nets; Management systems; New product; Optimal number; Price models; Simulation; Simulation tests; Strategic issues; Transaction cost; Decision making},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2006) On-line identification of discrete event systems: A case study IN 2006 IEEE International Conference on Automation Science and Engineering, CASE., 405 – 410. doi:10.1109/COASE.2006.326916
  [BibTeX] [Abstract] [Download PDF]

  The paper analyses an on-line identification strategy for Discrete Event Systems (DES) using Interpreted Petri Nets (IPN). The identifier stores a sequence of events and the corresponding output symbols and applies a recursive algorithm providing an IPN modeling the DES. Moreover, the identification procedure is based on the solution of an integer linear programming problem. In addition, we investigate on the conditions that lead to determine an IPN modeling the DES dynamics without error. Finally, simulation and analysis of a case study show the efficiency of the strategy. ©2006 IEEE.

  @CONFERENCE{Dotoli2006405,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello},
  title = {On-line identification of discrete event systems: A case study},
  year = {2006},
  journal = {2006 IEEE International Conference on Automation Science and Engineering, CASE},
  pages = {405 – 410},
  doi = {10.1109/COASE.2006.326916},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-45149130035&doi=10.1109%2fCOASE.2006.326916&partnerID=40&md5=66d5a530efd4a57ab359004be731da79},
  abstract = {The paper analyses an on-line identification strategy for Discrete Event Systems (DES) using Interpreted Petri Nets (IPN). The identifier stores a sequence of events and the corresponding output symbols and applies a recursive algorithm providing an IPN modeling the DES. Moreover, the identification procedure is based on the solution of an integer linear programming problem. In addition, we investigate on the conditions that lead to determine an IPN modeling the DES dynamics without error. Finally, simulation and analysis of a case study show the efficiency of the strategy. ©2006 IEEE.},
  author_keywords = {Discrete event systems; Identification; Integer linear programming; Petri nets},
  keywords = {Identification (control systems); Integer programming; Petri nets; Identification procedure; Integer Linear Programming; Interpreted Petri nets; On-line identification; Paper analysis; Recursive algorithms; Sequence of events; Simulation and analysis; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M. & Fanti, M. P. (2006) An urban traffic network model via coloured timed Petri nets. IN Control Engineering Practice, 14.1213 – 1229. doi:10.1016/j.conengprac.2006.02.005
  [BibTeX] [Abstract] [Download PDF]

  This paper deals with modelling of traffic networks (TNs) for control purposes. A modular framework based on coloured timed Petri nets (CTPNs) is proposed to model the dynamics of signalized TN systems: places represent link cells and crossing sections, tokens are vehicles and token colours represent the routing of the corresponding vehicle. In addition, ordinary timed Petri nets model the signal timing plans of the traffic lights controlling the area. The proposed modelling framework is applied to a real intersection located in Bari, Italy. A discrete event simulation of the controlled intersection validates the model and tests the signal timing plan obtained by an optimization strategy presented in the related literature. © 2006 Elsevier Ltd. All rights reserved.

  @ARTICLE{Dotoli20061213,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia},
  title = {An urban traffic network model via coloured timed Petri nets},
  year = {2006},
  journal = {Control Engineering Practice},
  volume = {14},
  number = {10},
  pages = {1213 – 1229},
  doi = {10.1016/j.conengprac.2006.02.005},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33744940832&doi=10.1016%2fj.conengprac.2006.02.005&partnerID=40&md5=305d401577efce152ce33d0d8cd605f2},
  abstract = {This paper deals with modelling of traffic networks (TNs) for control purposes. A modular framework based on coloured timed Petri nets (CTPNs) is proposed to model the dynamics of signalized TN systems: places represent link cells and crossing sections, tokens are vehicles and token colours represent the routing of the corresponding vehicle. In addition, ordinary timed Petri nets model the signal timing plans of the traffic lights controlling the area. The proposed modelling framework is applied to a real intersection located in Bari, Italy. A discrete event simulation of the controlled intersection validates the model and tests the signal timing plan obtained by an optimization strategy presented in the related literature. © 2006 Elsevier Ltd. All rights reserved.},
  author_keywords = {Discrete event systems; Modelling; Petri nets; Traffic control; Urban systems; Validation},
  keywords = {Computer simulation; Discrete time control systems; Intersections; Mathematical models; Optimization; Petri nets; Traffic control; Traffic signals; Computer simulation; Discrete time control systems; Intersections; Mathematical models; Optimization; Petri nets; Traffic signals; Discrete event systems; Traffic network model; Urban systems; Traffic control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 94}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2006) Modelling distributed manufacturing systems via first order hybrid petri nets . doi:10.3182/20060607-3-it-3902.00012
  [BibTeX] [Abstract] [Download PDF]

  This chapter proposes a new model for distributed manufacturing system (DMS) employing first order hybrid Petri nets that is Petri nets based on first order fluid approximation. A (DMS) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. Appropriate modeling and analysis of these highly complex systems are crucial for performance evaluation and comparison of competing DMS. However, few contributions face the problem of modeling the DMS in order to analyze the system performance measures and to optimize its functional objectives. The chapter considers First-Order Hybrid Petri Nets (FOHPN) to model distributed manufacturing systems (DMS), which are new emerging company networks, very complex to describe and manage. Combining continuous and discrete dynamics, FOHPN appears a promising formalism, able to capture the different properties of such discrete event systems, characterized by a large number of states. © 2006 Elsevier Ltd All rights reserved.

  @BOOK{Dotoli200644,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello},
  title = {Modelling distributed manufacturing systems via first order hybrid petri nets},
  year = {2006},
  journal = {Analysis and Design of Hybrid Systems 2006},
  pages = {44 – 49},
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  abstract = {This chapter proposes a new model for distributed manufacturing system (DMS) employing first order hybrid Petri nets that is Petri nets based on first order fluid approximation. A (DMS) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. Appropriate modeling and analysis of these highly complex systems are crucial for performance evaluation and comparison of competing DMS. However, few contributions face the problem of modeling the DMS in order to analyze the system performance measures and to optimize its functional objectives. The chapter considers First-Order Hybrid Petri Nets (FOHPN) to model distributed manufacturing systems (DMS), which are new emerging company networks, very complex to describe and manage. Combining continuous and discrete dynamics, FOHPN appears a promising formalism, able to capture the different properties of such discrete event systems, characterized by a large number of states. © 2006 Elsevier Ltd All rights reserved.},
  keywords = {Complex networks; Manufacture; Petri nets; Appropriate models; Distributed manufacturing systems; First order; First-order hybrid Petri nets; Fluid approximation; Modelling and analysis; Performance comparison; Storage systems; Transportation system; Via-first; Discrete event simulation},
  type = {Book chapter},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0; All Open Access, Bronze Open Access}
  }

• Dotoli, M., Fanti, M. P., Meloni, C. & Zhou, M. (2006) Service computing for design and reconfiguration of integrated e-supply chains . doi:10.4018/978-1-59904-180-3.ch013
  [BibTeX] [Abstract] [Download PDF]

  This chapter proposes a three-level decision-support system (DSS) for integrated e-supply-chains (IESCs) network design and reconfiguration based on data and information that can be obtained via Internet- and Web-based computing tools. The IESC is described as a set of consecutive stages connected by communication and transportation links, and the design and reconfiguration aim of the DSS consists of selecting the partners of the stages on the basis of transportation connections and information flows. More precisely, the first DSS level evaluates the performance of all the IESC candidates and singles out the best ones. The second DSS level solves a multicriteria integer linear optimization problem to configure the network. Finally, the third DSS level is devoted to evaluating and validating the solution proposed in the first two modules. The chapter proposes the use of some optimization techniques to synthesize the first two levels and illustrates the decision process by way of a case study. © 2007, Idea Group Inc.

  @BOOK{Dotoli2006322,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Meloni, Carlo and Zhou, Mengchu},
  title = {Service computing for design and reconfiguration of integrated e-supply chains},
  year = {2006},
  journal = {Enterprise Service Computing: From Concept to Deployment},
  pages = {322 – 354},
  doi = {10.4018/978-1-59904-180-3.ch013},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84900273298&doi=10.4018%2f978-1-59904-180-3.ch013&partnerID=40&md5=1782140aa690d7a2721383f64b4625d7},
  abstract = {This chapter proposes a three-level decision-support system (DSS) for integrated e-supply-chains (IESCs) network design and reconfiguration based on data and information that can be obtained via Internet- and Web-based computing tools. The IESC is described as a set of consecutive stages connected by communication and transportation links, and the design and reconfiguration aim of the DSS consists of selecting the partners of the stages on the basis of transportation connections and information flows. More precisely, the first DSS level evaluates the performance of all the IESC candidates and singles out the best ones. The second DSS level solves a multicriteria integer linear optimization problem to configure the network. Finally, the third DSS level is devoted to evaluating and validating the solution proposed in the first two modules. The chapter proposes the use of some optimization techniques to synthesize the first two levels and illustrates the decision process by way of a case study. © 2007, Idea Group Inc.},
  type = {Book chapter},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M., Fanti, M. P. & Meloni, C. (2006) A signal timing plan formulation for urban traffic control. IN Control Engineering Practice, 14.1297 – 1311. doi:10.1016/j.conengprac.2005.06.013
  [BibTeX] [Abstract] [Download PDF]

  This paper addresses urban traffic control using an optimization model for signalized areas. The paper modifies and extends a discrete time model for urban traffic networks proposed in the related literature to take into account some real aspects of traffic. The model is embedded in a real time controller that solves an optimization problem from the knowledge of some measurable inputs. Hence, the controller determines the signal timing plan on the basis of technical, physical, and operational constraints. The actuated control strategy is applied to a case study with severe traffic congestion, showing the effectiveness of the technique. © 2005 Elsevier Ltd. All rights reserved.

  @ARTICLE{Dotoli20061297,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Meloni, Carlo},
  title = {A signal timing plan formulation for urban traffic control},
  year = {2006},
  journal = {Control Engineering Practice},
  volume = {14},
  number = {11},
  pages = {1297 – 1311},
  doi = {10.1016/j.conengprac.2005.06.013},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33745223278&doi=10.1016%2fj.conengprac.2005.06.013&partnerID=40&md5=02a6705328b63ce182d71a23dc2aef18},
  abstract = {This paper addresses urban traffic control using an optimization model for signalized areas. The paper modifies and extends a discrete time model for urban traffic networks proposed in the related literature to take into account some real aspects of traffic. The model is embedded in a real time controller that solves an optimization problem from the knowledge of some measurable inputs. Hence, the controller determines the signal timing plan on the basis of technical, physical, and operational constraints. The actuated control strategy is applied to a case study with severe traffic congestion, showing the effectiveness of the technique. © 2005 Elsevier Ltd. All rights reserved.},
  author_keywords = {Discrete time systems; Optimization; Timing plan formulation; Urban traffic control; Urban traffic model},
  keywords = {Control equipment; Discrete time control systems; Embedded systems; Mathematical models; Optimization; Real time systems; Traffic control; Control equipment; Discrete time control systems; Embedded systems; Mathematical models; Optimization; Real time systems; Timing plan formulation; Urban traffic control; Urban traffic model; Traffic control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 112}
  }

• Dotoli, M., Fanti, M. P., Meloni, C. & Zhou, M. (2006) Design and optimization of integrated e-supply chain for agile and environmentally conscious manufacturing. IN IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, 36.62 – 75. doi:10.1109/TSMCA.2005.859189
  [BibTeX] [Abstract] [Download PDF]

  An agile and environmentally conscious manufacturing paradigm refers to the ability to reconfigure a flexible system quickly, economically, and environmentally responsibly. In modern manufacturing enterprises, e-supply chains integrate Internet and web-based electronic market and are promising systems to achieve agility. A key issue in the strategic logistic planning of integrated e-supply chains (IESCs) is the configuration of the partner network. This paper proposes a single- and multiobjective optimization model to configure the network of IESCs. Considering an Internet-based distributed manufacturing system composed of different stages connected by material and information links, a procedure is presented to select the appropriate links. A set of performance indices is associated with the network links. Single-criterion and multicriteria optimization models are presented under structural constraint definitions. The integer linear programming (ILP) problem solution provides different network structures that allow to improve supply chain (SC) flexibility, agility, and environmental performance in the design process. The proposed optimization strategy is applied to two case studies describing two networks for desktop computer production. © 2006 IEEE.

  @ARTICLE{Dotoli200662,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Meloni, Carlo and Zhou, MengChu},
  title = {Design and optimization of integrated e-supply chain for agile and environmentally conscious manufacturing},
  year = {2006},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans},
  volume = {36},
  number = {1},
  pages = {62 – 75},
  doi = {10.1109/TSMCA.2005.859189},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-30444455739&doi=10.1109%2fTSMCA.2005.859189&partnerID=40&md5=9d912f9ffe27450390dc4cd42da399db},
  abstract = {An agile and environmentally conscious manufacturing paradigm refers to the ability to reconfigure a flexible system quickly, economically, and environmentally responsibly. In modern manufacturing enterprises, e-supply chains integrate Internet and web-based electronic market and are promising systems to achieve agility. A key issue in the strategic logistic planning of integrated e-supply chains (IESCs) is the configuration of the partner network. This paper proposes a single- and multiobjective optimization model to configure the network of IESCs. Considering an Internet-based distributed manufacturing system composed of different stages connected by material and information links, a procedure is presented to select the appropriate links. A set of performance indices is associated with the network links. Single-criterion and multicriteria optimization models are presented under structural constraint definitions. The integer linear programming (ILP) problem solution provides different network structures that allow to improve supply chain (SC) flexibility, agility, and environmental performance in the design process. The proposed optimization strategy is applied to two case studies describing two networks for desktop computer production. © 2006 IEEE.},
  author_keywords = {Agile manufacturing; Computer integrated manufacturing; Integer linear programming; Optimization method; Supply chain; System analysis and design},
  keywords = {Computer integrated manufacturing; Electronic commerce; Integer programming; Internet; Linear programming; Mathematical models; Optimization; Systems analysis; Integer linear programming; Multiobjective optimization; Supply chain; Agile manufacturing systems},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 106; All Open Access, Bronze Open Access}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2006) Modelling distributed manufacturing systems via first order hybrid petri nets IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 44 – 49. doi:10.3182/20060607-3-it-3902.00012
  [BibTeX] [Abstract] [Download PDF]

  A Distributed Manufacturing System (DMS) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. This paper proposes a new model for DMS employing first order hybrid Petri nets, i.e., Petri nets based on first order fluid approximation. More precisely, transporters and manufacturers are described by continuous transitions, buffers are continuous places and products are represented by continuous flows routing from manufacturers, buffers and transporters. Moreover, discrete events occurring stochastically in the system are considered to take into account the start of the retailer requests and the blocking of transports and raw material supply. With the aim of showing the model effectiveness, a DMS example is modelled and simulated under two different operative conditions. Copyright © 2006 IFAC.

  @CONFERENCE{Dotoli200644,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello},
  title = {Modelling distributed manufacturing systems via first order hybrid petri nets},
  year = {2006},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {2},
  number = {PART 1},
  pages = {44 – 49},
  doi = {10.3182/20060607-3-it-3902.00012},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-40949127627&doi=10.3182%2f20060607-3-it-3902.00012&partnerID=40&md5=900e4cc6ae1bda58cd29c0478e5c1336},
  abstract = {A Distributed Manufacturing System (DMS) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. This paper proposes a new model for DMS employing first order hybrid Petri nets, i.e., Petri nets based on first order fluid approximation. More precisely, transporters and manufacturers are described by continuous transitions, buffers are continuous places and products are represented by continuous flows routing from manufacturers, buffers and transporters. Moreover, discrete events occurring stochastically in the system are considered to take into account the start of the retailer requests and the blocking of transports and raw material supply. With the aim of showing the model effectiveness, a DMS example is modelled and simulated under two different operative conditions. Copyright © 2006 IFAC.},
  author_keywords = {Dynamic models; Manufacturing systems; Performance indices; Petri-nets; Simulation},
  keywords = {Dynamic models; Hybrid systems; Petri nets; Continuous flows; Continuous transitions; Distributed manufacturing systems; First-order hybrid Petri nets; Fluid approximation; Performance indices; Raw material supply; Simulation; Manufacture},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3; All Open Access, Bronze Open Access}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2006) On-line identification of discrete event systems by interpreted Petri nets IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 3040 – 3045. doi:10.1109/ICSMC.2006.384582
  [BibTeX] [Abstract] [Download PDF]

  The paper proposes an on-line identification strategy for Discrete Event Systems (DES). The identifier stores a sequence of events and the corresponding output symbols. Moreover, by solving an integer linear programming problem, an identification procedure synthesizes an Interpreted Petri Net (IPN) modeling the DES. More precisely, we assume that the fixed numbers of places are given and that a finite sequence of transitions and the corresponding markings are completely or partially known. Moreover, the identification algorithm working in real-time identifies the IPN assuming the DES dynamics deterministic, i.e., the event occurrence from a given state yields only one new state. © 2006 IEEE.

  @CONFERENCE{Dotoli20063040,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello},
  title = {On-line identification of discrete event systems by interpreted Petri nets},
  year = {2006},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {4},
  pages = {3040 – 3045},
  doi = {10.1109/ICSMC.2006.384582},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-34548142248&doi=10.1109%2fICSMC.2006.384582&partnerID=40&md5=e6c11a6bac07fc58bb0b94492bc3a978},
  abstract = {The paper proposes an on-line identification strategy for Discrete Event Systems (DES). The identifier stores a sequence of events and the corresponding output symbols. Moreover, by solving an integer linear programming problem, an identification procedure synthesizes an Interpreted Petri Net (IPN) modeling the DES. More precisely, we assume that the fixed numbers of places are given and that a finite sequence of transitions and the corresponding markings are completely or partially known. Moreover, the identification algorithm working in real-time identifies the IPN assuming the DES dynamics deterministic, i.e., the event occurrence from a given state yields only one new state. © 2006 IEEE.},
  author_keywords = {Discrete event systems; Identification; Integer linear programming; Petri nets},
  keywords = {Algorithms; Identification (control systems); Integer programming; Mathematical models; Petri nets; Problem solving; Corresponding markings; DES dynamics; Identification procedure; Integer linear programming; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 5}
  }

• Dotoli, M. & Fanti, M. P. (2006) A generalized stochastic Petri net model for supply chain management. IN Mediterranean Journal of Measurement and Control, 2.1 – 11.
  [BibTeX] [Abstract] [Download PDF]

  A Supply Chain (SC) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. This paper deals with the issues of modeling and managing the SC at the operational level, in order to study the performance measures of the systems controlled by different management strategies. The system is modeled as a timed discrete event dynamical system, whose evolution depends on the interaction of discrete events such as the arrival of components at the facilities, the departure of the transporters from the suppliers or the manufacturers, the start of assembly operations at the manufacturers. More precisely, generalized stochastic Petri nets model the system in a modular way and describe its behavior. Moreover, two well known broad policies are considered to manage the SC: make-to-stock and make-to-order. In order to compare the two management strategies and to show the effectiveness of the modeling technique, a case study is presented. Copyright © 2006 SoftMotor Ltd.

  @ARTICLE{Dotoli20061,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia},
  title = {A generalized stochastic Petri net model for supply chain management},
  year = {2006},
  journal = {Mediterranean Journal of Measurement and Control},
  volume = {2},
  number = {1},
  pages = {1 – 11},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33645000427&partnerID=40&md5=9ec84b773c130b54bbb234bc558e895b},
  abstract = {A Supply Chain (SC) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. This paper deals with the issues of modeling and managing the SC at the operational level, in order to study the performance measures of the systems controlled by different management strategies. The system is modeled as a timed discrete event dynamical system, whose evolution depends on the interaction of discrete events such as the arrival of components at the facilities, the departure of the transporters from the suppliers or the manufacturers, the start of assembly operations at the manufacturers. More precisely, generalized stochastic Petri nets model the system in a modular way and describe its behavior. Moreover, two well known broad policies are considered to manage the SC: make-to-stock and make-to-order. In order to compare the two management strategies and to show the effectiveness of the modeling technique, a case study is presented. Copyright © 2006 SoftMotor Ltd.},
  author_keywords = {Discrete event systems; Management; Modeling; Performance evaluation; Petri nets; Supply chains},
  keywords = {Evaluation; Mathematical models; Performance; Petri nets; Random processes; Sales; Discrete event systems; Performance evaluation; Supply chains; Industrial management},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M., Fanti, M. P. & Mangini, A. M. (2006) An optimization approach for identification of Petri Nets IN Proceedings – Eighth International Workshop on Discrete Event Systems, WODES 2006., 332 – 337. doi:10.1109/wodes.2006.382528
  [BibTeX] [Abstract] [Download PDF]

  The paper addresses the identification problem of discrete event systems by determining the structure and the initial marking of a Petri Net (PN) modeling the system. More precisely, we assume that the numbers of places and of transitions are given and that a finite sequence of transitions and the corresponding markings are completely or partially known. Hence, the conditions to univocally identify a pure PN are established. On the other hand, if the singleness of the identification problem solution can not be guaranteed, we introduce an approach based on the solution of an integer linear programming problem. The linear constraint definition utilizes the knowledge of the observed firing sequence and the properties imposed on the PN. © 2006 IEEE.

  @CONFERENCE{Dotoli2006332,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Mangini, Agostino Marcello},
  title = {An optimization approach for identification of Petri Nets},
  year = {2006},
  journal = {Proceedings - Eighth International Workshop on Discrete Event Systems, WODES 2006},
  pages = {332 – 337},
  doi = {10.1109/wodes.2006.382528},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-34250667850&doi=10.1109%2fwodes.2006.382528&partnerID=40&md5=8565b0d1bfaf4e03e2b322549a4cc2a9},
  abstract = {The paper addresses the identification problem of discrete event systems by determining the structure and the initial marking of a Petri Net (PN) modeling the system. More precisely, we assume that the numbers of places and of transitions are given and that a finite sequence of transitions and the corresponding markings are completely or partially known. Hence, the conditions to univocally identify a pure PN are established. On the other hand, if the singleness of the identification problem solution can not be guaranteed, we introduce an approach based on the solution of an integer linear programming problem. The linear constraint definition utilizes the knowledge of the observed firing sequence and the properties imposed on the PN. © 2006 IEEE.},
  author_keywords = {Discrete event systems; Identification; Integer linear programming; Petri nets},
  keywords = {Identification (control systems); Integer programming; Linear programming; Optimization; Petri nets; Problem solving; Integer linear programming; Petri net modeling; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 13}
  }

• Costantino, N., Dotoli, M., Falagario, M., Fanti, M. P. & Iacobellis, G. (2006) Evaluating the total costs of purchasing via probabilistic and fuzzy reasoning. IN Fuzzy Economic Review, 11.69 – 92. doi:10.25102/fer.2006.01.05
  [BibTeX] [Abstract] [Download PDF]

  Transaction costs analysis is concerned with ways of aligning appropriate governance modes with the attributes of economic transactions. Nowadays transaction costs are universally accepted, despite the difficulty in measuring and quantifying them. Starting from the customary definition of transaction costs, this paper proposes a model for the buyer/seller relationship, focusing on the uncertainty characterizing the exchange and the connected costs. In particular, according to a well-known classification, the transaction costs connected to the purchasing phase are divided into ex ante (drafting and negotiating agreements) and ex post (monitoring and enforcing agree-ments) costs. More precisely, we propose to employ appropriate deterministic models for evaluating ex ante costs and suitable statistical distributions for ex post costs. Obviously, both such costs categories require the quantification of several parameters related to the buyer operating the transaction and to the uncertainty characterizing the buyer/ seller relationship. Hence, in order to correctly evaluate the buyer behavior, a fuzzy logic inference system is designned for synthesizing, starting from expert judgments, the required data to the transaction costs model. The reported simulation experiments show the effecttiveness of the proposed model in estimating the transaction costs and total costs associated with a generic transaction.

  @ARTICLE{Costantino200669,
  author = {Costantino, N. and Dotoli, M. and Falagario, M. and Fanti, M.P. and Iacobellis, G.},
  title = {Evaluating the total costs of purchasing via probabilistic and fuzzy reasoning},
  year = {2006},
  journal = {Fuzzy Economic Review},
  volume = {11},
  number = {1},
  pages = {69 – 92},
  doi = {10.25102/fer.2006.01.05},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015286388&doi=10.25102%2ffer.2006.01.05&partnerID=40&md5=d8957966363c53be3a282091ca99739b},
  abstract = {Transaction costs analysis is concerned with ways of aligning appropriate governance modes with the attributes of economic transactions. Nowadays transaction costs are universally accepted, despite the difficulty in measuring and quantifying them. Starting from the customary definition of transaction costs, this paper proposes a model for the buyer/seller relationship, focusing on the uncertainty characterizing the exchange and the connected costs. In particular, according to a well-known classification, the transaction costs connected to the purchasing phase are divided into ex ante (drafting and negotiating agreements) and ex post (monitoring and enforcing agree-ments) costs. More precisely, we propose to employ appropriate deterministic models for evaluating ex ante costs and suitable statistical distributions for ex post costs. Obviously, both such costs categories require the quantification of several parameters related to the buyer operating the transaction and to the uncertainty characterizing the buyer/ seller relationship. Hence, in order to correctly evaluate the buyer behavior, a fuzzy logic inference system is designned for synthesizing, starting from expert judgments, the required data to the transaction costs model. The reported simulation experiments show the effecttiveness of the proposed model in estimating the transaction costs and total costs associated with a generic transaction.},
  author_keywords = {Customized product; Fuzzy logic; Probabilistic reasoning; Standardized product; Total costs of purchasing; Transaction costs analysis},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 9}
  }

2005

• Dotoli, M. & Turchiano, B. (2005) Piecewise linear fuzzy sliding mode control. IN Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2955 LNAI.89 – 96.
  [BibTeX] [Abstract] [Download PDF]

  We present a novel fuzzy sliding mode control technique for a class of second order dynamical systems based on a piecewise linear sliding manifold. The proposed approach benefits from a reduction in the control action magnitude with respect to classical sliding mode control strategies, enhancing the effectiveness of such strategies under a saturated control input. In addition, employing the proposed fuzzy rule based algorithm results in smooth dynamics when the trajectory is in the vicinities of the sliding manifold. © Springer-Verlag Berlin Heidelberg 2006.

  @ARTICLE{Dotoli200589,
  author = {Dotoli, Mariagrazia and Turchiano, Biagio},
  title = {Piecewise linear fuzzy sliding mode control},
  year = {2005},
  journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
  volume = {2955 LNAI},
  pages = {89 – 96},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33744819206&partnerID=40&md5=8ac02a77c38c49e19700eaf72b3f85fc},
  abstract = {We present a novel fuzzy sliding mode control technique for a class of second order dynamical systems based on a piecewise linear sliding manifold. The proposed approach benefits from a reduction in the control action magnitude with respect to classical sliding mode control strategies, enhancing the effectiveness of such strategies under a saturated control input. In addition, employing the proposed fuzzy rule based algorithm results in smooth dynamics when the trajectory is in the vicinities of the sliding manifold. © Springer-Verlag Berlin Heidelberg 2006.},
  keywords = {Algorithms; Fuzzy sets; Linear systems; Control strategies; Mode control; Sliding manifold; Fuzzy control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M. & Fanti, M. P. (2005) A generalized stochastic petri net model for management of distributed manufacturing systems IN Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC ’05., 2125 – 2130. doi:10.1109/CDC.2005.1582475
  [BibTeX] [Abstract] [Download PDF]

  A Distributed Manufacturing System (DMS) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. This paper deals with the issues of modeling and managing a DMS. The system is modeled as a timed discrete event dynamical system by generalized stochastic Petri nets. Moreover, two well known broad policies are considered to manage the DMS: make-to-stock and make-to-order. In order to compare the two management techniques and to show the effectiveness of each method, a case study is presented. © 2005 IEEE.

  @CONFERENCE{Dotoli20052125,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia},
  title = {A generalized stochastic petri net model for management of distributed manufacturing systems},
  year = {2005},
  journal = {Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05},
  volume = {2005},
  pages = {2125 – 2130},
  doi = {10.1109/CDC.2005.1582475},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847191765&doi=10.1109%2fCDC.2005.1582475&partnerID=40&md5=7657f4e2cc93433f4daa4cc358d2a6b1},
  abstract = {A Distributed Manufacturing System (DMS) is a collection of independent companies possessing complementary skills and integrated with transportation and storage systems. This paper deals with the issues of modeling and managing a DMS. The system is modeled as a timed discrete event dynamical system by generalized stochastic Petri nets. Moreover, two well known broad policies are considered to manage the DMS: make-to-stock and make-to-order. In order to compare the two management techniques and to show the effectiveness of each method, a case study is presented. © 2005 IEEE.},
  keywords = {Computer simulation; Mathematical models; Random processes; Time varying control systems; Distributed manufacturing systems (DMS); Event dynamical systems; Storage systems; Petri nets},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6}
  }

• Dotoli, M. & Fanti, M. P. (2005) A coloured Petri net model for automated storage and retrieval systems serviced by rail-guided vehicles: A control perspective. IN International Journal of Computer Integrated Manufacturing, 18.122 – 136. doi:10.1080/0951192052000288233
  [BibTeX] [Abstract] [Download PDF]

  An Automated Storage and Retrieval System (AS/RS) automatically stores incoming material and retrieves stored parts with no direct human handling. This paper proposes a modular and unified modelling framework for heterogeneous automated storage and retrieval systems, comprising rail guided vehicles and narrow aisle cranes. We employ coloured timed Petri nets, representing a concise and computationally efficient tool for modelling the system dynamic behaviour, particularly suitable for real-time control implementation. Indeed, the model can be utilized in a discrete event simulation to apply control policies in order to solve scheduling problems, as well as to avoid deadlock and collision occurrences. © 2005 Taylor & Francis Ltd.

  @ARTICLE{Dotoli2005122,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia},
  title = {A coloured Petri net model for automated storage and retrieval systems serviced by rail-guided vehicles: A control perspective},
  year = {2005},
  journal = {International Journal of Computer Integrated Manufacturing},
  volume = {18},
  number = {2-3},
  pages = {122 – 136},
  doi = {10.1080/0951192052000288233},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-27944439698&doi=10.1080%2f0951192052000288233&partnerID=40&md5=b53075bf66067ae7616ef24e32c35622},
  abstract = {An Automated Storage and Retrieval System (AS/RS) automatically stores incoming material and retrieves stored parts with no direct human handling. This paper proposes a modular and unified modelling framework for heterogeneous automated storage and retrieval systems, comprising rail guided vehicles and narrow aisle cranes. We employ coloured timed Petri nets, representing a concise and computationally efficient tool for modelling the system dynamic behaviour, particularly suitable for real-time control implementation. Indeed, the model can be utilized in a discrete event simulation to apply control policies in order to solve scheduling problems, as well as to avoid deadlock and collision occurrences. © 2005 Taylor & Francis Ltd.},
  author_keywords = {Automated storage and retrieval systems; Coloured timed petri nets; Real-time control},
  keywords = {Computer simulation; Discrete time control systems; Information retrieval; Mathematical models; Problem solving; Real time systems; Automated storage and retrieval system; Coloured timed petri nets; Real-time control; Petri nets},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 49}
  }

• Dotoli, M., Fanti, M. P., Meloni, C. & Zhou, M. C. (2005) A multi-level approach for network design of integrated supply chains. IN International Journal of Production Research, 43.4267 – 4287. doi:10.1080/00207540500142316
  [BibTeX] [Abstract] [Download PDF]

  Integrated e-supply chains are distributed manufacturing systems composed of various resources belonging to different companies and integrated with streamlined material, information and financial flow. The configuration of the supply-chain network is essential for business to pursue a competitive advantage and to meet the market demand. This paper proposes a three-level hierarchical methodology for a supply chain network design at the planning-management level. The integrated supply chain network is described as a set of consecutive stages connected by communication and transportation links, and the configuration aim consists in selecting the actors of the stages on the basis of transportation connection and information flow. More precisely, the first level evaluates the performance of the entities candidate to join the network and singles out efficient elements. The second level solves a multi-criteria integer linear optimization problem to configure the network. Finally, the third level is devoted to evaluating and validating the solution proposed in the first two levels. The overall decision process is the result of the interaction of the modules that are dedicated to each decision level. The paper presents some optimization techniques to synthesize the first two levels and illustrates the hierarchical decision process by way of a case study.

  @ARTICLE{Dotoli20054267,
  author = {Dotoli, M. and Fanti, M.P. and Meloni, C. and Zhou, M.C.},
  title = {A multi-level approach for network design of integrated supply chains},
  year = {2005},
  journal = {International Journal of Production Research},
  volume = {43},
  number = {20},
  pages = {4267 – 4287},
  doi = {10.1080/00207540500142316},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-30444454095&doi=10.1080%2f00207540500142316&partnerID=40&md5=3337a1cf0287a0e4c7646a10c75554f6},
  abstract = {Integrated e-supply chains are distributed manufacturing systems composed of various resources belonging to different companies and integrated with streamlined material, information and financial flow. The configuration of the supply-chain network is essential for business to pursue a competitive advantage and to meet the market demand. This paper proposes a three-level hierarchical methodology for a supply chain network design at the planning-management level. The integrated supply chain network is described as a set of consecutive stages connected by communication and transportation links, and the configuration aim consists in selecting the actors of the stages on the basis of transportation connection and information flow. More precisely, the first level evaluates the performance of the entities candidate to join the network and singles out efficient elements. The second level solves a multi-criteria integer linear optimization problem to configure the network. Finally, the third level is devoted to evaluating and validating the solution proposed in the first two levels. The overall decision process is the result of the interaction of the modules that are dedicated to each decision level. The paper presents some optimization techniques to synthesize the first two levels and illustrates the hierarchical decision process by way of a case study.},
  author_keywords = {Distributed manufacturing systems; Integrated e-supply chains; Network design; Optimization},
  keywords = {Computer networks; Decision making; Manufacture; Optimization; Integrated e-supply chains; Network design; Industrial plants},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 82}
  }

• Dotoli, M., Fanti, M. P. & Iacobellis, G. (2005) Validation of an Urban traffic network model using Colored Timed Petri Nets IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 1347 – 1352.
  [BibTeX] [Abstract] [Download PDF]

  This paper validates a Colored Timed Petri Net (CTPN) model proposed to describe urban traffic networks. In particular, a CTPN models the dynamics of signalized traffic networks and timed Petri nets describe the traffic lights controlling the area. To this aim, the modeling framework is applied to a real intersection located in Bari, Italy. Discrete event simulations of the controlled intersection test the signal timing plan under different traffic scenarios and give a confirmation of the model capability to correctly predict the traffic performance. © 2005 IEEE.

  @CONFERENCE{Dotoli20051347,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio},
  title = {Validation of an Urban traffic network model using Colored Timed Petri Nets},
  year = {2005},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {2},
  pages = {1347 – 1352},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-27944461806&partnerID=40&md5=8e62875cc97fed230116bd127dd2cdb7},
  abstract = {This paper validates a Colored Timed Petri Net (CTPN) model proposed to describe urban traffic networks. In particular, a CTPN models the dynamics of signalized traffic networks and timed Petri nets describe the traffic lights controlling the area. To this aim, the modeling framework is applied to a real intersection located in Bari, Italy. Discrete event simulations of the controlled intersection test the signal timing plan under different traffic scenarios and give a confirmation of the model capability to correctly predict the traffic performance. © 2005 IEEE.},
  author_keywords = {Colored timed Petri nets; Modeling; Performance measures; Urban systems; Validation},
  keywords = {Computer simulation; Mathematical models; Petri nets; Signal processing; Telecommunication traffic; Colored timed Petri nets; Performance measures; Urban systems; Validation; Telecommunication systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 19}
  }

• Dotoli, M., Fanti, M. P., Meloni, C. & Zhou, M. C. (2005) Network design of integrated e-supply chain for agile manufacturing IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 31 – 36. doi:10.3182/20050703-6-cz-1902.01489
  [BibTeX] [Abstract] [Download PDF]

  Supply chains are distributed manufacturing systems composed of various resources belonging to different companies. The configuration of the supply chain network, integrated with Internet and web-based electronic market places, is essential for business to pursue a competitive advantage. This paper develops a model describing the integrated e-supply chain network and formulates a multi-criteria integer linear optimization problem to select the candidates and the links connecting the stages of the e-supply chain. Hence, some multi-criteria objective functions are defined and suited constraints are introduced on the basis of the digraph modelling the supply chain network. The proposed methodology is illustrated by way of a case study describing a network for desktop computer production. Copyright © 2005 IFAC.

  @CONFERENCE{Dotoli200531,
  author = {Dotoli, M. and Fanti, M.P. and Meloni, C. and Zhou, M.C.},
  title = {Network design of integrated e-supply chain for agile manufacturing},
  year = {2005},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {38},
  number = {1},
  pages = {31 – 36},
  doi = {10.3182/20050703-6-cz-1902.01489},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960727501&doi=10.3182%2f20050703-6-cz-1902.01489&partnerID=40&md5=47cecadcd65b0d45a600ccce4b161679},
  abstract = {Supply chains are distributed manufacturing systems composed of various resources belonging to different companies. The configuration of the supply chain network, integrated with Internet and web-based electronic market places, is essential for business to pursue a competitive advantage. This paper develops a model describing the integrated e-supply chain network and formulates a multi-criteria integer linear optimization problem to select the candidates and the links connecting the stages of the e-supply chain. Hence, some multi-criteria objective functions are defined and suited constraints are introduced on the basis of the digraph modelling the supply chain network. The proposed methodology is illustrated by way of a case study describing a network for desktop computer production. Copyright © 2005 IFAC.},
  author_keywords = {Agile manufacturing; Manufacturing systems; Networks; Optimization; Performance indices},
  keywords = {Competition; Electronics industry; Integer programming; Linear programming; Manufacture; Networks (circuits); Optimization; Supply chains; Agile manufacturing; Competitive advantage; Computer production; Distributed manufacturing systems; Linear optimization problems; Objective functions; Performance indices; Supply chain network; Agile manufacturing systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M., Fanti, M. P., Mangini, A. M. & Tempone, G. (2005) Fuzzy multi-objective optimization for network design of logistic and production systems IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA., 475 – 482.
  [BibTeX] [Abstract] [Download PDF]

  Global competition has given rise to Logistic and Production Systems (LPSs), that are distributed manufacturing systems integrating international logistics and information technologies with production. This paper builds upon an LPS network design model previously proposed by some of the authors. The recalled technique formulates and solves a multi-criteria optimization problem to select the partners in the different stages of the production chain and the links connecting them. In this paper, in order to rank the equally optimal Pareto solutions of such a problem, we propose to employ fuzzy multi-criteria optimization. Two fuzzification techniques and two different multicriteria methods are considered. In addition, the methodology is illustrated by way of a case study. Moreover, a discussion on the different advantages and limitations of the proposed techniques is provided. © 2005 IEEE.

  @CONFERENCE{Dotoli2005475,
  author = {Dotoli, M. and Fanti, M.P. and Mangini, A.M. and Tempone, G.},
  title = {Fuzzy multi-objective optimization for network design of logistic and production systems},
  year = {2005},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  volume = {1 2 VOLS},
  pages = {475 – 482},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33847291232&partnerID=40&md5=8f8cde691d6827bb90c053c68be08948},
  abstract = {Global competition has given rise to Logistic and Production Systems (LPSs), that are distributed manufacturing systems integrating international logistics and information technologies with production. This paper builds upon an LPS network design model previously proposed by some of the authors. The recalled technique formulates and solves a multi-criteria optimization problem to select the partners in the different stages of the production chain and the links connecting them. In this paper, in order to rank the equally optimal Pareto solutions of such a problem, we propose to employ fuzzy multi-criteria optimization. Two fuzzification techniques and two different multicriteria methods are considered. In addition, the methodology is illustrated by way of a case study. Moreover, a discussion on the different advantages and limitations of the proposed techniques is provided. © 2005 IEEE.},
  author_keywords = {Fuzzy logic; Logistic and production systems; Network design; Optimization; Performance indices},
  keywords = {Computer aided manufacturing; Mathematical models; Optimization; Pareto principle; Production control; Distributed manufacturing systems; Logistic and Production Systems (LPS); Network designs; Performance indices; Fuzzy control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

2004

• Dotoli, M. & Fanti, M. P. (2004) Coloured timed Petri net model for real-time control of automated guided vehicle systems. IN International Journal of Production Research, 42.1787 – 1814. doi:10.1080/00207540410001661364
  [BibTeX] [Abstract] [Download PDF]

  Automated guided vehicle systems (AGVS) are material-handling devices representing an efficient and flexible option for products management in automated manufacturing systems. In AGVS, vehicles follow a guide-path while controlled by a computer that assigns the route, tasks, velocity, etc. Moreover, the design of AGVS has to take into account some management problems such as collisions and deadlocks. The paper presents a novel control strategy to avoid deadlock and collisions in zone-controlled AGVS. In particular, the control scheme manages the assignments of new paths to vehicles and their acquisition of the next zone. Moreover, the use of coloured Petri nets is proposed to model the dynamics of AGVS and implement the control strategy stemming from the knowledge of the system state. Additionally, extending the coloured Petri net model with a time concept allows investigation of system performance. Several simulations of an AGVS with varying fleet size while measuring appropriate performance indices show the effectiveness of the proposed control strategy compared with an alternative policy previously presented.

  @ARTICLE{Dotoli20041787,
  author = {Dotoli, M. and Fanti, M.P.},
  title = {Coloured timed Petri net model for real-time control of automated guided vehicle systems},
  year = {2004},
  journal = {International Journal of Production Research},
  volume = {42},
  number = {9},
  pages = {1787 – 1814},
  doi = {10.1080/00207540410001661364},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-1942536568&doi=10.1080%2f00207540410001661364&partnerID=40&md5=9d7743286dd86cc38a18992d8dfd27a3},
  abstract = {Automated guided vehicle systems (AGVS) are material-handling devices representing an efficient and flexible option for products management in automated manufacturing systems. In AGVS, vehicles follow a guide-path while controlled by a computer that assigns the route, tasks, velocity, etc. Moreover, the design of AGVS has to take into account some management problems such as collisions and deadlocks. The paper presents a novel control strategy to avoid deadlock and collisions in zone-controlled AGVS. In particular, the control scheme manages the assignments of new paths to vehicles and their acquisition of the next zone. Moreover, the use of coloured Petri nets is proposed to model the dynamics of AGVS and implement the control strategy stemming from the knowledge of the system state. Additionally, extending the coloured Petri net model with a time concept allows investigation of system performance. Several simulations of an AGVS with varying fleet size while measuring appropriate performance indices show the effectiveness of the proposed control strategy compared with an alternative policy previously presented.},
  keywords = {Algorithms; Automation; Computational complexity; Computer control; Computer simulation; Computer software; Data acquisition; Decision making; Flexible manufacturing systems; Laws and legislation; Materials handling; Motion planning; Petri nets; Product design; Specifications; Strategic planning; Automated guided vehicle syatem (AGVS); Automated manufacturing systems (AMS); Real-time control; Computer integrated manufacturing},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 42}
  }

• Dotoli, M., Fanti, M. P. & Meloni, C. (2004) Coordination and real time optimization of signal timing plans for urban traffic control IN Conference Proceeding – IEEE International Conference on Networking, Sensing and Control., 1069 – 1074.
  [BibTeX] [Abstract] [Download PDF]

  An effective method to improve traffic flow in urban areas is synchronizing the traffic signals at the coordinated intersections. This paper focuses on the problem of synchronization of subsequent intersections in a signalized urban area. Adopting an optimization model proposed in literature, the paper investigates the determination of the offset between two signals, i.e., the time displacements of green splits along a movement direction. On the basis of traffic observations, appropriate selection of offset in two coordinated intersections located in an urban area is performed under different congestion scenarios. Results show the efficiency of the proposed method to allow uninterrupted flow of traffic.

  @CONFERENCE{Dotoli20041069,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Meloni, Carlo},
  title = {Coordination and real time optimization of signal timing plans for urban traffic control},
  year = {2004},
  journal = {Conference Proceeding - IEEE International Conference on Networking, Sensing and Control},
  volume = {2},
  pages = {1069 – 1074},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-2942670188&partnerID=40&md5=3c36cdf2ba797cacbfb56a366431d4b5},
  abstract = {An effective method to improve traffic flow in urban areas is synchronizing the traffic signals at the coordinated intersections. This paper focuses on the problem of synchronization of subsequent intersections in a signalized urban area. Adopting an optimization model proposed in literature, the paper investigates the determination of the offset between two signals, i.e., the time displacements of green splits along a movement direction. On the basis of traffic observations, appropriate selection of offset in two coordinated intersections located in an urban area is performed under different congestion scenarios. Results show the efficiency of the proposed method to allow uninterrupted flow of traffic.},
  author_keywords = {Green phases optimization; Offset determination; Signalized urban area; Traffic control},
  keywords = {Bandwidth; Computer simulation; Mathematical models; Real time systems; Signaling; Synchronization; Traffic control; Green phase optimization; Offset determination; Signalized urban area; Urban planning},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 11}
  }

• Dotoli, M. & Fanti, M. P. (2004) An urban traffic network model via coloured timed petri nets IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 207 – 212. doi:10.1016/S1474-6670(17)30747-4
  [BibTeX] [Abstract] [Download PDF]

  This paper deals with modelling of traffic networks for real time control purposes. A modular framework based on coloured timed Petri nets is proposed to model the dynamics of signalized traffic network systems: places represent link cells and crossing sections, tokens are vehicles and token colours represent the routing of the corresponding vehicle. In addition, an ordinary timed Petri net models the signal timing plan controlling the area. The proposed modelling framework is applied to a real intersection located in Bari, Italy. A discrete event simulation of the controlled intersection validates the model and tests the signal timing plan obtained by an optimization strategy presented in the related literature. © 2004 IFAC.

  @CONFERENCE{Dotoli2004207,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia},
  title = {An urban traffic network model via coloured timed petri nets},
  year = {2004},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {37},
  number = {18},
  pages = {207 – 212},
  doi = {10.1016/S1474-6670(17)30747-4},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051827290&doi=10.1016%2fS1474-6670%2817%2930747-4&partnerID=40&md5=0f9a5a59070094d9b6b85645f801e0b7},
  abstract = {This paper deals with modelling of traffic networks for real time control purposes. A modular framework based on coloured timed Petri nets is proposed to model the dynamics of signalized traffic network systems: places represent link cells and crossing sections, tokens are vehicles and token colours represent the routing of the corresponding vehicle. In addition, an ordinary timed Petri net models the signal timing plan controlling the area. The proposed modelling framework is applied to a real intersection located in Bari, Italy. A discrete event simulation of the controlled intersection validates the model and tests the signal timing plan obtained by an optimization strategy presented in the related literature. © 2004 IFAC.},
  author_keywords = {Discrete event systems; Modelling; Petri-nets; Road traffic; Traffic control},
  keywords = {Models; Petri nets; Real time control; Traffic control; Traffic signals; Coloured timed petri nets; Modelling framework; Modular framework; Optimization strategy; Road traffic; Signal timing plan; Traffic networks; Urban traffic networks; Discrete event simulation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10; All Open Access, Bronze Open Access}
  }

• Dotoli, M., Fanti, M. P. & Meloni, C. (2004) Candidate selection for network design of distributed manufacturing systems IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 1613 – 1618. doi:10.1109/ICSMC.2004.1399862
  [BibTeX] [Abstract] [Download PDF]

  Supply chains are distributed manufacturing systems composed of various resources belonging to different companies. Efficient design of the supply chain network is essential for business to pursue a competitive advantage. In this paper a hierarchical methodology previously outlined by the authors is considered for supply chain network design. In the first level, the performance of the entities candidate to join the network is evaluated and efficient elements are singled out. The second level is aimed at developing a model to configure the network. Finally, the third level is devoted to validating the solution proposed in the first two levels. The paper focuses on the first level and proposes a four-step procedure to select the candidates in the supply chain stages. Some optimization multi-criteria techniques are considered and the proposed decision level is illustrated by way of a case study describing a network for desktop computer production. © 2004 IEEE.

  @CONFERENCE{Dotoli20041613,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Meloni, Carlo},
  title = {Candidate selection for network design of distributed manufacturing systems},
  year = {2004},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {2},
  pages = {1613 – 1618},
  doi = {10.1109/ICSMC.2004.1399862},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-15744388734&doi=10.1109%2fICSMC.2004.1399862&partnerID=40&md5=3879606fdd5bd17a1cd000b6c126b155},
  abstract = {Supply chains are distributed manufacturing systems composed of various resources belonging to different companies. Efficient design of the supply chain network is essential for business to pursue a competitive advantage. In this paper a hierarchical methodology previously outlined by the authors is considered for supply chain network design. In the first level, the performance of the entities candidate to join the network is evaluated and efficient elements are singled out. The second level is aimed at developing a model to configure the network. Finally, the third level is devoted to validating the solution proposed in the first two levels. The paper focuses on the first level and proposes a four-step procedure to select the candidates in the supply chain stages. Some optimization multi-criteria techniques are considered and the proposed decision level is illustrated by way of a case study describing a network for desktop computer production. © 2004 IEEE.},
  author_keywords = {Candidate selection; Decision making; Distributed manufacturing; Network design; Supply chain management},
  keywords = {Computer simulation; Data reduction; Decision making; Internet; Mathematical models; Schematic diagrams; Candidate selection; Distributed manufacturing; Network design; Supply chain management (SCM); Computer aided manufacturing},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Brunettil, C. & Dotoli, M. (2004) Rule-Based decoupled fuzzy sliding mode control for inverted pendulum Swing-Up IN IEEE International Symposium on Industrial Electronics., 495 – 500. doi:10.1109/ISIE.2004.1571857
  [BibTeX] [Abstract] [Download PDF]

  In this paper we introduce a novel decoupled fuzzy sliding mode (DFSM) controller for swinging-up an inverted pendulum. In the proposed technique the control objective is decomposed into two sub-tasks: swing-up and stabilization. Accordingly, first a DFSM controller stabilizing the poles is synthesized. Next, a rule-based regulator dealing with the task of entering a stabilization zone is svnthesized. Two different structures are proposed for the swing-up controller. In the first strategy the control action is obtained by a crisp approach, while in the second one the controller is based on fuzzy rules. Experimental tests show, the effectiveness of the proposed strategy for swinging-up an inverted pendulum with restricted cart travel and limited control action.©2004 IEEE.

  @CONFERENCE{Brunettil2004495,
  author = {Brunettil, Celestino and Dotoli, Mariagrazia},
  title = {Rule-Based decoupled fuzzy sliding mode control for inverted pendulum Swing-Up},
  year = {2004},
  journal = {IEEE International Symposium on Industrial Electronics},
  volume = {1},
  pages = {495 – 500},
  doi = {10.1109/ISIE.2004.1571857},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-34249094952&doi=10.1109%2fISIE.2004.1571857&partnerID=40&md5=282a7d773d902529a98fb3b80f119d79},
  abstract = {In this paper we introduce a novel decoupled fuzzy sliding mode (DFSM) controller for swinging-up an inverted pendulum. In the proposed technique the control objective is decomposed into two sub-tasks: swing-up and stabilization. Accordingly, first a DFSM controller stabilizing the poles is synthesized. Next, a rule-based regulator dealing with the task of entering a stabilization zone is svnthesized. Two different structures are proposed for the swing-up controller. In the first strategy the control action is obtained by a crisp approach, while in the second one the controller is based on fuzzy rules. Experimental tests show, the effectiveness of the proposed strategy for swinging-up an inverted pendulum with restricted cart travel and limited control action.©2004 IEEE.},
  author_keywords = {Decoupled Fuzzy Sliding Mode Control; Fuzzy sliding Mode Control; Inverted Pendulum on a Cart; Stabilization; Swing-up},
  keywords = {Fuzzy control; Industrial electronics; Pendulums; Sliding mode control; Stabilization; Control actions; Control objectives; Decoupled Fuzzy Sliding Mode Control; Different structure; Experimental test; Fuzzy sliding mode; Fuzzy sliding Mode Control; Inverted pendulum; Inverted Pendulum on a Cart; Rule based; Stabilization zone; Subtasks; Swing-up; Controllers},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 3}
  }

• Dotoli, M., Fanti, M. P. & Iacobellis, G. (2004) Comparing deadlock detection and avoidance policies in automated storage and retrieval systems IN Conference Proceedings – IEEE International Conference on Systems, Man and Cybernetics., 1607 – 1612. doi:10.1109/ICSMC.2004.1399861
  [BibTeX] [Abstract] [Download PDF]

  This paper focuses on real time control of Automated Storage and Retrieval Systems (AS/RSs), that is in charge of making decisions on resource allocation and scheduling choices. In these systems deadlock conditions may occur when parts require a set of resources in a circular wait situation. We model a generic multi-product AS/RSs serviced by rail guided vehicles as a discrete event system. Next, we compare two different real time deadlock solution strategies for AS/RSs: a deadlock avoidance strategy previously proposed by one of the authors and a deadlock detection/recovery strategy, proposed in the related literature. The considered control strategies are compared by means of a simulation of a case study. © 2004 IEEE.

  @CONFERENCE{Dotoli20041607,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Iacobellis, Giorgio},
  title = {Comparing deadlock detection and avoidance policies in automated storage and retrieval systems},
  year = {2004},
  journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
  volume = {2},
  pages = {1607 – 1612},
  doi = {10.1109/ICSMC.2004.1399861},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-15744380812&doi=10.1109%2fICSMC.2004.1399861&partnerID=40&md5=e5a224d4b0fad5c785eb5600a9d8242b},
  abstract = {This paper focuses on real time control of Automated Storage and Retrieval Systems (AS/RSs), that is in charge of making decisions on resource allocation and scheduling choices. In these systems deadlock conditions may occur when parts require a set of resources in a circular wait situation. We model a generic multi-product AS/RSs serviced by rail guided vehicles as a discrete event system. Next, we compare two different real time deadlock solution strategies for AS/RSs: a deadlock avoidance strategy previously proposed by one of the authors and a deadlock detection/recovery strategy, proposed in the related literature. The considered control strategies are compared by means of a simulation of a case study. © 2004 IEEE.},
  author_keywords = {Automated storage and retrieval systems; Deadlock avoidance; Deadlock detection; Discrete event simulation; Real time control},
  keywords = {Computer simulation; Computer system recovery; Decision making; Materials handling; Real time systems; Resource allocation; Scheduling; Automated storage and retrieval systems; Deadlock avoidance; Deadlock detection; Discrete event simulation; Real time control; Computer control systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 7}
  }

2003

• Dotoli, M. & Fanti, M. P. (2003) Performance of two real time control strategies for AGV systems: A case study IN European Control Conference, ECC 2003., 3171 – 3176. doi:10.23919/ecc.2003.7086527
  [BibTeX] [Abstract] [Download PDF]

  Real time control of material handling devices is essential to guarantee efficiency and flexibility of automated manufacturing systems. This paper presents a performance based comparison of two control policies previously presented by one of the authors to avoid deadlock and collisions in zone controlled Automated Guided Vehicle Systems (AGVSs). Coloured Timed Petri Nets are used to model the dynamics of AGVSs and implement the control strategies stemming from the knowledge of the system state. Several simulations of an AGVS with varying fleet size show the effectiveness of one of the considered control strategies compared to the alternative policy. © 2003 EUCA.

  @CONFERENCE{Dotoli20033171,
  author = {Dotoli, M. and Fanti, M.P.},
  title = {Performance of two real time control strategies for AGV systems: A case study},
  year = {2003},
  journal = {European Control Conference, ECC 2003},
  pages = {3171 – 3176},
  doi = {10.23919/ecc.2003.7086527},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949111912&doi=10.23919%2fecc.2003.7086527&partnerID=40&md5=37b20fa0d244bb4ca77b90f6985aca18},
  abstract = {Real time control of material handling devices is essential to guarantee efficiency and flexibility of automated manufacturing systems. This paper presents a performance based comparison of two control policies previously presented by one of the authors to avoid deadlock and collisions in zone controlled Automated Guided Vehicle Systems (AGVSs). Coloured Timed Petri Nets are used to model the dynamics of AGVSs and implement the control strategies stemming from the knowledge of the system state. Several simulations of an AGVS with varying fleet size show the effectiveness of one of the considered control strategies compared to the alternative policy. © 2003 EUCA.},
  author_keywords = {Automated guided vehicle systems; Coloured timed Petri nets; Deadlock avoidance; Discrete event simulation; Real time control},
  keywords = {Automatic guided vehicles; Automation; Discrete event simulation; Manufacture; Materials handling; Mobile robots; Petri nets; Real time control; Automated guided vehicle system; Automated manufacturing systems; Coloured timed petri nets; Control strategies; Deadlock avoidance; Material handling; Performance based; Real-time control strategy; Discrete time control systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M. (2003) Fuzzy sliding mode control with piecewise linear switching manifold. IN Asian Journal of Control, 5.528 – 542. doi:10.1111/j.1934-6093.2003.tb00170.x
  [BibTeX] [Abstract] [Download PDF]

  Variable Structure Control (VSC) has been successfully established in control systems engineering in the past two decades. Recently, Fuzzy Sliding Mode Control (FSMC) techniques have drawn the attention of the scientific community, due to their effectiveness in reducing the typical chattering phenomenon arising in VSC. We present a novel FSMC technique for a class of second order dynamical systems based on a piecewise linear sliding manifold. The proposed approach enhances the effectiveness of VSC in the presence of a saturated control input. In addition, employing the proposed VSC with fuzzy rule based algorithms results in smooth dynamics when the trajectory is in the vicinity of the switching manifold, as opposed to the typical chattering arising under classical VSC. After illustrating the proposed strategy on a simple design example, the approach is applied to an inverted pendulum, a well-known benchmark for automatic control techniques. The effectiveness of the technique is shown both by means of simulation tests and experiments on a lab equipment. Future research directions include the extension of the technique in the presence of uncertainties in the plant model.

  @ARTICLE{Dotoli2003528,
  author = {Dotoli, Mariagrazia},
  title = {Fuzzy sliding mode control with piecewise linear switching manifold},
  year = {2003},
  journal = {Asian Journal of Control},
  volume = {5},
  number = {4},
  pages = {528 – 542},
  doi = {10.1111/j.1934-6093.2003.tb00170.x},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-2942618414&doi=10.1111%2fj.1934-6093.2003.tb00170.x&partnerID=40&md5=56eeb4322e87edb24e4af810595afc62},
  abstract = {Variable Structure Control (VSC) has been successfully established in control systems engineering in the past two decades. Recently, Fuzzy Sliding Mode Control (FSMC) techniques have drawn the attention of the scientific community, due to their effectiveness in reducing the typical chattering phenomenon arising in VSC. We present a novel FSMC technique for a class of second order dynamical systems based on a piecewise linear sliding manifold. The proposed approach enhances the effectiveness of VSC in the presence of a saturated control input. In addition, employing the proposed VSC with fuzzy rule based algorithms results in smooth dynamics when the trajectory is in the vicinity of the switching manifold, as opposed to the typical chattering arising under classical VSC. After illustrating the proposed strategy on a simple design example, the approach is applied to an inverted pendulum, a well-known benchmark for automatic control techniques. The effectiveness of the technique is shown both by means of simulation tests and experiments on a lab equipment. Future research directions include the extension of the technique in the presence of uncertainties in the plant model.},
  author_keywords = {Fuzzy sliding mode control; Inverted pendulum; Nonlinear systems; Switching surface; Variable structure control},
  keywords = {Control theory; Fuzzy control; Nonlinear control systems; Chattering; Inverted pendulum; Switching surface; Variable structure control; Sliding mode control},
  type = {Article},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 7}
  }

• Dotoli, M., Fanti, M. P. & Meloni, C. (2003) Real time optimization of traffic signal control: Application to coordinated intersections IN Proceedings of the IEEE International Conference on Systems, Man and Cybernetics., 3288 – 3295.
  [BibTeX] [Abstract] [Download PDF]

  This paper investigates the issue of urban traffic signal control using a real time optimization model for signalized areas proposed in the related literature. The adopted model is modified to take into account the traffic scenarios, the different types of vehicles in the area, as well as pedestrians. The technique is applied to a real case study, consisting of two coordinated intersections located in the urban area of Bari (Italy). On the basis of traffic observations, optimal selection of the phases in the semaphoric cycle is performed under different congestion scenarios. Results show the ability of the strategy to minimize the vehicle queue lengths in the area.

  @CONFERENCE{Dotoli20033288,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia and Meloni, Carlo},
  title = {Real time optimization of traffic signal control: Application to coordinated intersections},
  year = {2003},
  journal = {Proceedings of the IEEE International Conference on Systems, Man and Cybernetics},
  volume = {4},
  pages = {3288 – 3295},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0242552639&partnerID=40&md5=00d2c8314d0ed059fa2464fe4e53d678},
  abstract = {This paper investigates the issue of urban traffic signal control using a real time optimization model for signalized areas proposed in the related literature. The adopted model is modified to take into account the traffic scenarios, the different types of vehicles in the area, as well as pedestrians. The technique is applied to a real case study, consisting of two coordinated intersections located in the urban area of Bari (Italy). On the basis of traffic observations, optimal selection of the phases in the semaphoric cycle is performed under different congestion scenarios. Results show the ability of the strategy to minimize the vehicle queue lengths in the area.},
  author_keywords = {Green phases optimization; Semaphoric cycle; Signalized area; Traffic control; Urban traffic},
  keywords = {Accidents; Intersections; Optimization; Traffic signals; Green phases optimization; Semaphoric cycle; Signalized area; Traffic control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 15}
  }

• Dotoli, M., Lino, P. & Turchiano, B. (2003) A decoupled fuzzy sliding mode approach to swing-up and stabilize an inverted pendulum IN IFAC Proceedings Volumes (IFAC-PapersOnline)., 113 – 118. doi:10.1016/S1474-6670(17)34654-2
  [BibTeX] [Abstract] [Download PDF]

  In this paper we present a novel decoupled fuzzy sliding mode (DFSM) strategy for swinging-up an inverted pendulum. In the proposed technique the control objective is decomposed into two sub-tasks, i.e., swing-up and stabilization. Accordingly, first a DFSM controller stabilizing the pole is synthesized and optimised via genetic algorithms. Next, a DFSM controller with a piecewise linear sliding manifold is synthesized and optimised, dealing with the task of entering the stabilization zone. Numerical simulations show the effectiveness of the proposed controller for a model encompassing friction as well as a limited control action and a restricted cart travel. © 2003 IFAC.

  @CONFERENCE{Dotoli2003113,
  author = {Dotoli, Mariagrazia and Lino, Paolo and Turchiano, Biagio},
  title = {A decoupled fuzzy sliding mode approach to swing-up and stabilize an inverted pendulum},
  year = {2003},
  journal = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
  volume = {36},
  number = {18},
  pages = {113 – 118},
  doi = {10.1016/S1474-6670(17)34654-2},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902000954&doi=10.1016%2fS1474-6670%2817%2934654-2&partnerID=40&md5=7a0b9376e0cf7ee5685ee6e526aae86b},
  abstract = {In this paper we present a novel decoupled fuzzy sliding mode (DFSM) strategy for swinging-up an inverted pendulum. In the proposed technique the control objective is decomposed into two sub-tasks, i.e., swing-up and stabilization. Accordingly, first a DFSM controller stabilizing the pole is synthesized and optimised via genetic algorithms. Next, a DFSM controller with a piecewise linear sliding manifold is synthesized and optimised, dealing with the task of entering the stabilization zone. Numerical simulations show the effectiveness of the proposed controller for a model encompassing friction as well as a limited control action and a restricted cart travel. © 2003 IFAC.},
  author_keywords = {Decoupled subsystems; Fuzzy control; Genetic algorithms; Nonlinear systems; Sliding mode control},
  keywords = {Fuzzy control; Fuzzy systems; Genetic algorithms; Nonlinear systems; Pendulums; Piecewise linear techniques; Sliding mode control; Stabilization; Control actions; Control objectives; Decoupled subsystems; Fuzzy sliding mode; Inverted pendulum; Piecewise linear; Sliding manifolds; Stabilization zone; Controllers},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 6; All Open Access, Bronze Open Access}
  }

• Dotoli, M. & Fanti, M. P. (2003) Performance-based comparison of control policies for automated storage and retrieval systems modelled by coloured Petri nets IN IEEE International Conference on Emerging Technologies and Factory Automation, ETFA., 299 – 306. doi:10.1109/ETFA.2003.1247721
  [BibTeX] [Abstract] [Download PDF]

  The industrial manufacturing environment is nowadays characterized by fierce global competition, rapid market changes and short product life cycles. Such a complex scenario originated a vast demand for sophisticated techniques guaranteeing adequate planning and control of warehouses. A widely used solution is to adopt Automated Storage and Retrieval Systems (AS/RSs). A typical AS/RS comprises a number of parallel aisles with storage racks, serviced by automated stacker cranes and rail guided vehicles. This paper compares several management strategies addressing the system operational control, i.e., dealing with the AS/RS real time behaviour. A common coloured timed Petri net models the system and the controlled AS/RS operation is highlighted by way of several discrete event simulations carried out in the Matlab-Stateflow software environment. The proposed control policies are compared and discussed on the basis of appropriate performance indices. © 2003 IEEE.

  @CONFERENCE{Dotoli2003299,
  author = {Dotoli, M. and Fanti, M.P.},
  title = {Performance-based comparison of control policies for automated storage and retrieval systems modelled by coloured Petri nets},
  year = {2003},
  journal = {IEEE International Conference on Emerging Technologies and Factory Automation, ETFA},
  volume = {1},
  number = {January},
  pages = {299 – 306},
  doi = {10.1109/ETFA.2003.1247721},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938546339&doi=10.1109%2fETFA.2003.1247721&partnerID=40&md5=a9fe6d6c02ddf626de46af5112688fff},
  abstract = {The industrial manufacturing environment is nowadays characterized by fierce global competition, rapid market changes and short product life cycles. Such a complex scenario originated a vast demand for sophisticated techniques guaranteeing adequate planning and control of warehouses. A widely used solution is to adopt Automated Storage and Retrieval Systems (AS/RSs). A typical AS/RS comprises a number of parallel aisles with storage racks, serviced by automated stacker cranes and rail guided vehicles. This paper compares several management strategies addressing the system operational control, i.e., dealing with the AS/RS real time behaviour. A common coloured timed Petri net models the system and the controlled AS/RS operation is highlighted by way of several discrete event simulations carried out in the Matlab-Stateflow software environment. The proposed control policies are compared and discussed on the basis of appropriate performance indices. © 2003 IEEE.},
  keywords = {Amphibious vehicles; Automatic guided vehicles; Automation; Competition; Computer control systems; Discrete event simulation; Factory automation; Information retrieval; MATLAB; Petri nets; Warehouses; Automated storage and retrieval system; Coloured Petri Nets; Industrial manufacturing; Management strategies; Operational control; Performance indices; Planning and control; Software environments; Life cycle},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 10}
  }

• Dotoli, M., Fanti, M. P., Meloni, C. & Zhou, M. C. (2003) A decision support system for the supply chain configuration IN Proceedings of the IEEE International Conference on Systems, Man and Cybernetics., 2667 – 2672.
  [BibTeX] [Abstract] [Download PDF]

  The design of a supply chain network provides the main structure for supply chain operations, since the network is a key element in the competitiveness and investments of an extended production system. The configuration of the network is essential for business to pursue a competitive advantage. We adopt a methodology based on three layers. In the first layer, the performance of the entities candidate to join the network is evaluated and efficient elements are individuated. The second layer develops a model to configure the network. Finally, the third layer is devoted to evaluate and validate the solution proposed in the first two levels. The overall decision process is the result of the interaction of the modules dedicated to each decision layer.

  @CONFERENCE{Dotoli20032667,
  author = {Dotoli, M. and Fanti, M.P. and Meloni, C. and Zhou, M.C.},
  title = {A decision support system for the supply chain configuration},
  year = {2003},
  journal = {Proceedings of the IEEE International Conference on Systems, Man and Cybernetics},
  volume = {3},
  pages = {2667 – 2672},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0242552830&partnerID=40&md5=62fdf601b57939ca4dd7d107c6c1ce3f},
  abstract = {The design of a supply chain network provides the main structure for supply chain operations, since the network is a key element in the competitiveness and investments of an extended production system. The configuration of the network is essential for business to pursue a competitive advantage. We adopt a methodology based on three layers. In the first layer, the performance of the entities candidate to join the network is evaluated and efficient elements are individuated. The second layer develops a model to configure the network. Finally, the third layer is devoted to evaluate and validate the solution proposed in the first two levels. The overall decision process is the result of the interaction of the modules dedicated to each decision layer.},
  author_keywords = {Decision support systems; Network design; Supply chain management},
  keywords = {Algorithms; Electronic commerce; Information technology; Performance; Network design; Supply chain configuration; Supply chain network; Decision support systems},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 15}
  }

2002

• Dotoli, M. & Fanti, M. P. (2002) Modeling of an AS/RS serviced by rail-guided vehicles with colored petri nets: A control perspective IN Proceedings of the IEEE International Conference on Systems, Man and Cybernetics., 160 – 165.
  [BibTeX] [Abstract] [Download PDF]

  An Automated Storage and Retrieval System (AS/RS) automatically stores incoming material and retrieves stored parts with no direct human handling. This paper proposes a modular and unified modeling framework for heterogeneous automated storage and retrieval systems, comprising rail guided vehicles and narrow aisle cranes. We employ colored timed Petri nets, representing a concise and computationally efficient tool for modeling the system dynamic behavior, particularly suitable for real time control implementation. Indeed, the model can be utilized in a discrete event simulation to apply control policies in order to solve scheduling problems, as well as to avoid deadlock and collision occurrences.

  @CONFERENCE{Dotoli2002160,
  author = {Dotoli, Mariagrazia and Fanti, Maria Pia},
  title = {Modeling of an AS/RS serviced by rail-guided vehicles with colored petri nets: A control perspective},
  year = {2002},
  journal = {Proceedings of the IEEE International Conference on Systems, Man and Cybernetics},
  volume = {3},
  pages = {160 – 165},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0037670107&partnerID=40&md5=a333a442bf1c4576e09002880b69aa89},
  abstract = {An Automated Storage and Retrieval System (AS/RS) automatically stores incoming material and retrieves stored parts with no direct human handling. This paper proposes a modular and unified modeling framework for heterogeneous automated storage and retrieval systems, comprising rail guided vehicles and narrow aisle cranes. We employ colored timed Petri nets, representing a concise and computationally efficient tool for modeling the system dynamic behavior, particularly suitable for real time control implementation. Indeed, the model can be utilized in a discrete event simulation to apply control policies in order to solve scheduling problems, as well as to avoid deadlock and collision occurrences.},
  author_keywords = {Automated storage and retrieval systems; Colored timed Petri nets; Real time control},
  keywords = {Computer control; Computer simulation; Computer system recovery; Crane rails; Petri nets; Real time systems; Remotely operated vehicles; Scheduling; Automated storage and retrieval systems (AS/RS); Railroads},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 18}
  }

• Dotoli, M., Gattagrisi, M., Pisani, C. D. & Turchiano, B. (2002) Automatic changeover of unwinding coils in copper wires stranding machines: A case study IN IECON Proceedings (Industrial Electronics Conference)., 2491 – 2496. doi:10.1109/IECON.2002.1185365
  [BibTeX] [Abstract] [Download PDF]

  In this paper we design an automatic changeover system for unwinding coils in copper wires stranding machines for energy cables. The system is illustrated by means of a case study: the stranding department at one of the plants of Pirelli Cables & Systems, the leader manufacturer in the field in Italy. Motivations for the study are increase in production, improvement in manpower utilization and decrease in waste material. Two alternative changeover algorithms are proposed and highlighted by means of simulations. Additionally, three different technical solutions are suggested, with several recommendations for implementations. Finally, a performance evaluation is carried out, investigating the impact of the study on the plant.

  @CONFERENCE{Dotoli20022491,
  author = {Dotoli, Mariagrazia and Gattagrisi, Maurizio and Pisani, Cosimo Damiano and Turchiano, Biagio},
  title = {Automatic changeover of unwinding coils in copper wires stranding machines: A case study},
  year = {2002},
  journal = {IECON Proceedings (Industrial Electronics Conference)},
  volume = {3},
  pages = {2491 – 2496},
  doi = {10.1109/IECON.2002.1185365},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036957151&doi=10.1109%2fIECON.2002.1185365&partnerID=40&md5=be2677d68a525b754b3094e4b7c1bbe3},
  abstract = {In this paper we design an automatic changeover system for unwinding coils in copper wires stranding machines for energy cables. The system is illustrated by means of a case study: the stranding department at one of the plants of Pirelli Cables & Systems, the leader manufacturer in the field in Italy. Motivations for the study are increase in production, improvement in manpower utilization and decrease in waste material. Two alternative changeover algorithms are proposed and highlighted by means of simulations. Additionally, three different technical solutions are suggested, with several recommendations for implementations. Finally, a performance evaluation is carried out, investigating the impact of the study on the plant.},
  keywords = {Copper; Electric coils; Winding machines; Wire drawing; Automatic changeover system; Copper wires; Stranding machines; Unwinding coils; Factory automation},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 1}
  }

• Dotoli, M. & Lino, P. (2002) Fuzzy adaptive control of a variable geometry turbocharged diesel engine IN IEEE International Symposium on Industrial Electronics., 1295 – 1300. doi:10.1109/isie.2002.1025977
  [BibTeX] [Abstract] [Download PDF]

  A fuzzy control approach for the adjustment of the boost pressure of a Variable Geometry Turbine (VGT) supercharged Diesel engine is proposed. The VGT adapts the boost pressure to the target reference for different enginc speeds by adjusting the turbine blades, resulting in a reduction of both fuel consumption and gas emissions, while preserving efficiency. We design an adaptive fuzzy control law according to the following steps: first, a standard PI controller is devised, then an equivalent fuzzy controller is built, finally the fuzzy controller is made non linear by tuning its input/output parameters using an optimization algorithm. Further, modification of the membership functions is investigated. A large number of simulations on a zero-dimensional model of the engine prove the effectiveness of the proposed control strategy with reference to stability and transient performance in comparison with standard PI techniques. © 2002 IEEE.

  @CONFERENCE{Dotoli20021295,
  author = {Dotoli, Mariagrazia and Lino, Paolo},
  title = {Fuzzy adaptive control of a variable geometry turbocharged diesel engine},
  year = {2002},
  journal = {IEEE International Symposium on Industrial Electronics},
  volume = {4},
  pages = {1295 – 1300},
  doi = {10.1109/isie.2002.1025977},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-63049123943&doi=10.1109%2fisie.2002.1025977&partnerID=40&md5=56238212cf4f75bbe5511c3a462e1fbc},
  abstract = {A fuzzy control approach for the adjustment of the boost pressure of a Variable Geometry Turbine (VGT) supercharged Diesel engine is proposed. The VGT adapts the boost pressure to the target reference for different enginc speeds by adjusting the turbine blades, resulting in a reduction of both fuel consumption and gas emissions, while preserving efficiency. We design an adaptive fuzzy control law according to the following steps: first, a standard PI controller is devised, then an equivalent fuzzy controller is built, finally the fuzzy controller is made non linear by tuning its input/output parameters using an optimization algorithm. Further, modification of the membership functions is investigated. A large number of simulations on a zero-dimensional model of the engine prove the effectiveness of the proposed control strategy with reference to stability and transient performance in comparison with standard PI techniques. © 2002 IEEE.},
  keywords = {Control theory; Diesel engines; Fuzzy control; Gas emissions; Industrial electronics; Membership functions; Turbomachine blades; Adaptive fuzzy control; Fuzzy-adaptive control; Optimization algorithms; Supercharged diesel engines; Transient performance; Turbocharged diesel engine; Variable geometry turbines; Zero-dimensional models; Controllers},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 5}
  }

• Cupertino, F., Dotoli, M., Giordano, V., Maione, B. & Salvatore, L. (2002) Fuzzy control experiments on DC drives using various inference connectives IN IEEE International Conference on Fuzzy Systems., 52 – 57.
  [BibTeX] [Abstract] [Download PDF]

  In this paper we investigate the functionality of fuzzy inference connectives for control. In particular, we employ selected conjunction, implication and aggregation operators, extensively used in the specialized literature, for speed control of a DC drive. The problem is approached from a practical perspective: we analyze the effect of the different connectives on the rise time performance index of the speed response obtained both in simulation and laboratory tests. Rather than the mere optimization of the DC drive, the object of the paper is the analysis of the key Fuzzy Controller (FC) features, in order to carry out an in-depth study of the FC operation and take full advantage of its potential.

  @CONFERENCE{Cupertino200252,
  author = {Cupertino, Francesco and Dotoli, Mariagrazia and Giordano, Vincenzo and Maione, Bruno and Salvatore, Luigi},
  title = {Fuzzy control experiments on DC drives using various inference connectives},
  year = {2002},
  journal = {IEEE International Conference on Fuzzy Systems},
  volume = {1},
  pages = {52 – 57},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036454069&partnerID=40&md5=aa981671262091b57f2585038048d64c},
  abstract = {In this paper we investigate the functionality of fuzzy inference connectives for control. In particular, we employ selected conjunction, implication and aggregation operators, extensively used in the specialized literature, for speed control of a DC drive. The problem is approached from a practical perspective: we analyze the effect of the different connectives on the rise time performance index of the speed response obtained both in simulation and laboratory tests. Rather than the mere optimization of the DC drive, the object of the paper is the analysis of the key Fuzzy Controller (FC) features, in order to carry out an in-depth study of the FC operation and take full advantage of its potential.},
  keywords = {Algorithms; Computer simulation; Control system analysis; DC motors; Electric drives; Optimization; Performance; Speed control; Fuzzy inference; Rise time performance index; Fuzzy control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 7}
  }

2001

• Dotoli, M., Maione, B., Naso, D. & Turchiano, B. (2001) Fuzzy sliding mode control for inverted pendulum swing-up with restricted travel IN IEEE International Conference on Fuzzy Systems., 753 – 756.
  [BibTeX] [Abstract] [Download PDF]

  Swinging up an inverted pendulum is a common benchmark task for the investigation of automatic control techniques. In this paper we introduce a new Fuzzy Sliding Mode (FSM) technique for swinging-up an inverted pendulum and controlling the connected cart, while minimizing the swing-up time, the cart travel and the required control action. The FSM technique adopted is based on a piecewise linear sliding manifold that is bent towards the far off zones of the pole phase plane, thus enabling the reduction of the control action. Further, in order to limit the cart overshoot two variable gains were inserted in the cart controller. We tested our technique both on a nonlinear model, including friction, and on a lab equipment: we report both on the upwards stabilization and swing-up. The pendulum upwards equilibrium point was made globally stable.

  @CONFERENCE{Dotoli2001753,
  author = {Dotoli, Mariagrazia and Maione, Bruno and Naso, David and Turchiano, Biagio},
  title = {Fuzzy sliding mode control for inverted pendulum swing-up with restricted travel},
  year = {2001},
  journal = {IEEE International Conference on Fuzzy Systems},
  volume = {2},
  pages = {753 – 756},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036343235&partnerID=40&md5=bce5d14c9a31ac1797cd83c3a76e5a9d},
  abstract = {Swinging up an inverted pendulum is a common benchmark task for the investigation of automatic control techniques. In this paper we introduce a new Fuzzy Sliding Mode (FSM) technique for swinging-up an inverted pendulum and controlling the connected cart, while minimizing the swing-up time, the cart travel and the required control action. The FSM technique adopted is based on a piecewise linear sliding manifold that is bent towards the far off zones of the pole phase plane, thus enabling the reduction of the control action. Further, in order to limit the cart overshoot two variable gains were inserted in the cart controller. We tested our technique both on a nonlinear model, including friction, and on a lab equipment: we report both on the upwards stabilization and swing-up. The pendulum upwards equilibrium point was made globally stable.},
  keywords = {Adaptive control systems; Gain control; Mathematical models; Motion control; Nonlinear control systems; Pendulums; Piecewise linear techniques; Sliding mode control; Stabilization; Fuzzy sliding mode control; Inverted pendulum; Piecewise linear sliding manifold; Fuzzy control},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 7}
  }

• Dotoli, M., Axer, H., Berks, G., Südfeld, D., Prescher, A., Keyserlingk, D. G. V., Krombach, G. A., Dounias, G., Panagi, G. M., Tselentis, G. & Jantzen, J. (2001) Teaching soft computing in medicine: An interdisciplinary experiment IN Annual Conference of the North American Fuzzy Information Processing Society – NAFIPS., 1979 – 1984.
  [BibTeX] [Abstract] [Download PDF]

  The objective of this study was to test the feasibility of teaching some of the many engineering applications within medicine to medical students together with engineering students. A summer school was created in a block-course design that lasted one week. Different teaching modules were divided into lecture and exercise sessions. Several engineering topics combined with medical examples were presented. Half of the students were engineering or computer science students and the other half medical students. The staff of lecturers was also mixed. At the end of the course the students had to pass a web-based examination and fill out an online evaluation-sheet. Most of the students regarded the co-operation between physicians and engineers as very important. The major challenge of the course was the interdisciplinary aspect of teaching: medical students had to learn about methods of information technology and engineering students were exposed to medical information analysis. Teaching both groups of students together resulted in a close collaboration between both groups. The paper highlights some pitfalls and gives recommendations for a similar type of course. In particular, the main recommendation for the future, given the technological advances in medicine, is a closer co-operation with disciplines such as information technology.

  @CONFERENCE{Dotoli20011979,
  author = {Dotoli, Mariagrazia and Axer, Hubertus and Berks, Georg and Südfeld, Dagmar and Prescher, Andreas and Keyserlingk, Diedrich Graf V. and Krombach, Gabriele A. and Dounias, George and Panagi, Georgia M. and Tselentis, George and Jantzen, Jan},
  title = {Teaching soft computing in medicine: An interdisciplinary experiment},
  year = {2001},
  journal = {Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS},
  volume = {4},
  pages = {1979 – 1984},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035792445&partnerID=40&md5=95f185aa6ad60a85c1e43de60c0d88b3},
  abstract = {The objective of this study was to test the feasibility of teaching some of the many engineering applications within medicine to medical students together with engineering students. A summer school was created in a block-course design that lasted one week. Different teaching modules were divided into lecture and exercise sessions. Several engineering topics combined with medical examples were presented. Half of the students were engineering or computer science students and the other half medical students. The staff of lecturers was also mixed. At the end of the course the students had to pass a web-based examination and fill out an online evaluation-sheet. Most of the students regarded the co-operation between physicians and engineers as very important. The major challenge of the course was the interdisciplinary aspect of teaching: medical students had to learn about methods of information technology and engineering students were exposed to medical information analysis. Teaching both groups of students together resulted in a close collaboration between both groups. The paper highlights some pitfalls and gives recommendations for a similar type of course. In particular, the main recommendation for the future, given the technological advances in medicine, is a closer co-operation with disciplines such as information technology.},
  keywords = {Artificial intelligence; Computer science; Engineering; Information technology; Medicine; Students; Teaching; World Wide Web; Lecture; Medical information analysis; Physicians; Soft computing; Medical computing},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 0}
  }

• Dotoli, M., Maione, G., Naso, D. & Turchiano, B. (2001) Genetic identification of dynamical systems with static nonlinearities IN SMCia 2001 – Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications., 65 – 70. doi:10.1109/SMCIA.2001.936730
  [BibTeX] [Abstract] [Download PDF]

  This paper describes the application of genetic algorithms (GA) to identify a class of nonlinear SISO models composed of a memoryless nonlinearity in series with a linear transfer function. In contrast with recent literature on the considered problem, we encode in the chromosomes also the structure of the model (type of nonlinearity, number of zeros and poles), and use the GA to identify both the optimal structure and the associated parameters. New operators for mutation and crossover to deal with chromosomes with variable length are introduced. The effectiveness of the approach is tested on a set of case studies derived from literature. © 2001 IEEE.

  @CONFERENCE{Dotoli200165,
  author = {Dotoli, M. and Maione, G. and Naso, D. and Turchiano, B.},
  title = {Genetic identification of dynamical systems with static nonlinearities},
  year = {2001},
  journal = {SMCia 2001 - Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications},
  pages = {65 – 70},
  doi = {10.1109/SMCIA.2001.936730},
  url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952771046&doi=10.1109%2fSMCIA.2001.936730&partnerID=40&md5=1c49976e5d4ecedc7f1c89f3b95314de},
  abstract = {This paper describes the application of genetic algorithms (GA) to identify a class of nonlinear SISO models composed of a memoryless nonlinearity in series with a linear transfer function. In contrast with recent literature on the considered problem, we encode in the chromosomes also the structure of the model (type of nonlinearity, number of zeros and poles), and use the GA to identify both the optimal structure and the associated parameters. New operators for mutation and crossover to deal with chromosomes with variable length are introduced. The effectiveness of the approach is tested on a set of case studies derived from literature. © 2001 IEEE.},
  keywords = {Algorithms; Chromosomes; Dynamical systems; Soft computing; Structural optimization; Case-studies; Genetic identification; Linear transfer function; Memoryless nonlinearities; Number of zeros; Optimal structures; Static non-linearity; Variable length; Genetic algorithms},
  type = {Conference paper},
  publication_stage = {Final},
  source = {Scopus},
  note = {Cited by: 23}
  }