Graziana CAVONE


Biografia

Graziana Cavone ha conseguito la Laurea con lode in Ingegneria dell’Automazione nel 2013 presso il Politecnico di Bari e il Dottorato di Ricerca (eccellente con lode) in Ingegneria Elettronica e Informatica nel 2018 presso l’Università degli Studi di Cagliari. Attualmente è assegnista di ricerca post-dottorato presso il Politecnico di Bari. È stata assegnista di ricerca nel 2014 presso il Politecnico di Bari e Visiting Ph.D. Student nel 2016-2017 presso la Delft University of Technology, Olanda. I suoi interessi di ricerca includono modellazione, simulazione, ottimizzazione e controllo di sistemi ibridi e ad eventi discreti, controllo distribuito, sistemi di produzione automatizzata, trasporto intelligente, Smart City.

È local Arrangements Chair della 2021 Mediterranean Conference on Control and Automation. È Associate Editor per la rivista internazionale Results in Control and Optimization (RICO). È stata membro dell’International Program Committee di oltre 20 conferenze internazionali e Guest Editor per special issues su riviste internazionali. È vincitrice di una research fellowship dalla National Science Foundation of China per l’anno 2020.

Temi di ricerca

  • automation;
  • optimization;
  • discrete event industrial systems;
  • decision and control systems;
  • modeling and optimization of complex systems;
  • petri nets;
  • manufacturing systems;
  • supply chains;
  • logistics and transportation systems;
  • traffic networks.

Pubblicazioni

2021

  • 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, G. and Carli, R. and Troccoli, G. and Tresca, G. and Dotoli, M.},
    title={A MILP approach for the multi-drop container loading problem resolution in logistics 4.0},
    journal={2021 29th Mediterranean Conference on Control and Automation, MED 2021},
    year={2021},
    pages={687-692},
    doi={10.1109/MED51440.2021.9480359},
    art_number={9480359},
    note={cited By 0},
    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},
    references={Strandhagen, J.O., Vallandingham, L.R., Fragapane, G., Strandhagen, J.W., Stangeland, A.B.H., Sharma, N., Logistics 4. 0 and emerging sustainable business models (2017) Advances in Manufacturing, 5 (4), pp. 359-369; Digiesi, S., Facchini, F., Mossa, G., Mummolo, G., Minimizing and balancing ergonomic risk of workers of an assembly line by job rotation: A minlp model (2018) International Journal of Industrial Engineering and Management, 9 (3), pp. 129-138; Bischoff, E.E., Ratcliff, M., Issues in the development of approaches to container loading (1995) Omega, 23 (4), pp. 377-390; Facchini, F., Digiesi, S., Mossa, G., Optimal dry port configuration for container terminals: A non-linear model for sustainable decision making (2020) International Journal of Production Economics, 219, pp. 164-178; Wäscher, G., Haußner, H., Schumann, H., An improved typology of cutting and packing problems (2007) European Journal of Operational Research, 183 (3), pp. 1109-1130; Bortfeldt, A., Wäscher, G., Constraints in container loading-a stateof-the-art review (2013) European Journal of Operational Research, 229 (1), pp. 1-20; Scheithauer, G., Terno, J., Riehme, J., Sommerweiss, U., A new heuristic approach for solving the multi-pallet packing problem (1996) Dresden: Technische Universität Dresden; Pisinger, D., Heuristics for the container loading problem (2002) European Journal of Operational Research, 141 (2), pp. 382-392; Moura, A., Oliveira, J.F., A grasp approach to the container-loading problem (2005) IEEE Intelligent Systems, 20 (4), pp. 50-57; Jin, Z., Ohno, K., Du, J., An efficient approach for the threedimensional container packing problem with practical constraints (2004) Asia-Pacific Journal of Operational Research, 21 (3), pp. 279-295; Lin, J.-L., Chang, C.-H., Yang, J.-Y., A study of optimal system for multiple-constraint multiple-container packing problems (2006) International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, pp. 1200-1210. , Springer; Ceschia, S., Schaerf, A., Local search for a multi-drop multicontainer loading problem (2013) Journal of Heuristics, 19 (2), pp. 275-294; Alonso, M., Alvarez-Valdes, R., Iori, M., Parreño, F., Mathematical models for multi container loading problems with practical constraints (2019) Computers & Industrial Engineering, 127, pp. 722-733; Do Nascimento, O.X., De Queiroz, T.A., Junqueira, L., Practical constraints in the container loading problem: Comprehensive formulations and exact algorithm (2021) Computers & Operations Research, 128, p. 105186; Dotoli, M., Epicoco, N., Falagario, M., Seatzu, C., Turchiano, B., A decision support system for optimizing operations at intermodal railroad terminals (2016) IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47 (3), pp. 487-501; Dotoli, M., Epicoco, N., A technique for the optimal management of containers' drayage at intermodal terminals (2016) 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, pp. 000566-000571; Junqueira, L., Morabito, R., Yamashita, D.S., Mip-based approaches for the container loading problem with multi-drop constraints (2012) Annals of Operations Research, 199 (1), pp. 51-75; Lai, K., Xue, J., Xu, B., Container packing in a multi-customer delivering operation (1998) Computers & Industrial Engineering, 35 (1-2), pp. 323-326; Christensen, S.G., Rousøe, D.M., Container loading with multidrop constraints (2009) International Transactions in Operational Research, 16 (6), pp. 727-743; Bemporad, A., Morari, M., Control of systems integrating logic, dynamics, and constraints (1999) Automatica, 35 (3), pp. 407-427},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, G. and Epicoco, N. and Carli, R. and Del Zotti, A. and Paulo Ribeiro Pereira, J. and Dotoli, M.},
    title={Parcel delivery with drones: Multi-criteria analysis of trendy system architectures},
    journal={2021 29th Mediterranean Conference on Control and Automation, MED 2021},
    year={2021},
    pages={693-698},
    doi={10.1109/MED51440.2021.9480332},
    art_number={9480332},
    note={cited By 0},
    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},
    references={Facchini, F., Digiesi, S., Mossa, G., Optimal dry port configuration for container terminals: A non-linear model for sustainable decision making (2020) Int. J. Prod. Econ., 219, pp. 164-178; Bhatti, A., Akram, H., Basit, H., Khan, A., Mahwish, S., Naqvi, R., Bilal, M., E-commerce trends during COVID-19 pandemic (2020) Int. J. Future Gener. Commun. Netw., 13; Ranieri, L., Digiesi, S., Silvestri, B., Roccotelli, M., A review of last mile logistics innovations in an externalities cost reduction vision (2018) Sustainability, 10 (782); Amazon Testing Drones for Deliveries, , www.bbc.com, accessed: 2021-01-04; Jung, S., Kim, H., Analysis of amazon prime air UAV delivery service (2017) J. Knowl. Inf. Technol. Syst., 12, pp. 253-266; Guerrero, M.E., Mercado, D., Lozano, R., García, C., Passivity based control for a quadrotor UAV transporting a cable-suspended payload with minimum swing (2015) 54th IEEE Conf. Decision and Control. IEEE, pp. 6718-6723; Peterson, K., Dektas, M., (2017) Ups Tests Residential Delivery Via Drone Launched from Atop Package Car, , www.pressroom.ups.com; Carlsson, J.G., Song, S., Coordinated logistics with a truck and a drone (2018) Manage. Sci., 64 (9), pp. 4052-4069; Lee, T., Geometric control of quadrotor uavs transporting a cablesuspended rigid body (2017) IEEE Trans. Control Syst. Technol., 26 (1), pp. 255-264; Park, S., Zhang, L., Chakraborty, S., Battery assignment and scheduling for drone delivery businesses (2017) IEEE/ACM Int. Symp. Low Power Electronics and Design. IEEE, pp. 1-6; Dorling, K., Heinrichs, J., Messier, G.G., Magierowski, S., Vehicle routing problems for drone delivery (2016) IEEE Trans. Syst. Man Cybern. Syst., 47 (1), pp. 70-85; Gatteschi, V., Lamberti, F., Paravati, G., Sanna, A., Demartini, C., Lisanti, A., Venezia, G., New frontiers of delivery services using drones: A prototype system exploiting a quadcopter for autonomous drug shipments (2015) 39th IEEE Ann. Computer Software and Applications Conf., 2, pp. 920-927; Charnes, A., Cooper, W., Rhodes, E., Measuring the efficiency of decision making units (1978) Eur. J. Oper. Res., 2 (6), pp. 429-444; Dotoli, M., Epicoco, N., Falagario, M., Multi-criteria decision making techniques for the management of public procurement tenders: A case study (2020) Appl. Soft Comput., 88. , 106064; Dotoli, M., Epicoco, N., Falagario, M., Sciancalepore, F., A crossefficiency fuzzy data envelopment analysis technique for performance evaluation of decision making units under uncertainty (2015) Comput. Ind. Eng., 79, pp. 103-114; Sexton, T.R., Silkman, R.H., Hogan, A.J., Data envelopment analysis: Critique and extensions (1986) Measuring Efficiency: An Assessment of Data Envelopment Analysis, pp. 73-105. , R. H. Silkman, Ed. San Francisco, CA: Jossey-Bass; Guo, R., Dong, Y., Meiqiang, W., Yongjun, L., Dea cross-efficiency evaluation method based on good relationship (2015) Int. J. Syst. Sci., 3 (1), pp. 14-24; Jeong, H.Y., Song, B.D., Lee, S., Truck-drone hybrid delivery routing: Payload-energy dependency and no-fly zones (2019) Int. J. Prod. Econ., 214, pp. 220-233; Linnik, I., (2018) How to Implement Drone Delivery Service for An Ecommerce Store, , www.onilab.com; Kesteloo, H., (2018) Drone Delivery Patent Issued to Workhorse for Their Horsefly Truck Launched Drone Package Delivery System, , www.dronedj.com; Murthy, J.G., Harshith, P.S., Joel, J.A., Rakesh, K., Sharath Kumar, A.J., Autonomous drone delivery system: A survey (2020) Int. Res. J. Eng. Technol., 7 (3), pp. 762-766; Ducato, , www.fiatprofessional.com, in Italian, accessed: 2021-01-04; www.planzer.ch, in Italian, accessed: 2021-01-04; Joshi, A., Kale, S., Chandel, S., Pal, D., Likert scale: Explored and explained (2015) Br. J. Appl. Sci. Technol., 7, pp. 396-403; Google Maps, , www.google.it/maps, accessed: 2021-01-04; Orlando, C., (2020) Prezzi Carburanti: Costo Benzina, Diesel, Gpl e Metano. Petrolio in Ribasso, , www.money.it, in Italian; I Prezzi Luce in Italia e all'Estero, , www.sorgenia.it, in Italian, accessed: 2021-01-04; EcoTransIT World, , www.ecotransit.org, accessed: 2021-01-04; Meet the Coolest Robots Working in Energy, , www.equinor.com, accessed: 2021-01-04; Vallecchi, L., (2019) Auto Elettriche e Diesel, un Confronto Su Emissioni di CO2 e Inquinanti, , www.qualenergia.it, in Italian},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, P. and Carli, R. and Cavone, G. and Epicoco, N. and Dotoli, M.},
    title={Modeling, estimation, and analysis of COVID-19 secondary waves: The Case of the Italian Country},
    journal={2021 29th Mediterranean Conference on Control and Automation, MED 2021},
    year={2021},
    pages={794-800},
    doi={10.1109/MED51440.2021.9480319},
    art_number={9480319},
    note={cited By 0},
    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},
    references={World Health Organization, , https://www.who.int/emergencies/diseases/novel-coronavirus-2019, Accessed: 2021-01-14; Mojur, M., Fattah, I.R., Alam, M.A., Islam, A.S., Ong, H.C., Rahman, S.A., Naja, G., Mahlia, T., Impact of COVID-19 on the social, economic, environmental and energy domains: Lessons learnt from a global pandemic (2021) Sustainable Production and Consumption, 26, pp. 343-359; Auriemma, V., Iannaccone, C., COVID-19 pandemic: Socioeconomic consequences of social distancing measures in Italy (2020) Fron-tiers in Sociology, 5, p. 78; Paré, P.E., Beck, C.L., Başar, T., Modeling, estimation, and analysis of epidemics over networks: An overview (2020) Annu. Rev. Control, 50, pp. 345-360; Calaore, G.C., Novara, C., Possieri, C., A time-varying sird model for the COVID-19 contagion in Italy (2020) Annual Reviews in Control, 50, pp. 361-372; Ding, Y., Gao, L., An evaluation of COVID-19 in Italy: A data-driven modeling analysis (2020) Infectious Disease Modelling, 5, pp. 495-501; Loli Piccolomini, E., Zama, F., Monitoring Italian COVID-19 spread by a forced seird model (2020) PLoS ONE, 15 (8), p. 0237417; Della Rossa, F., Salzano, D., Di Meglio, A., De Lellis, F., A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic (2020) Nat. Commun., 11, p. 5106; Carli, R., Cavone, G., Epicoco, N., Scarabaggio, P., Dotoli, M., Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario (2020) Annu. Rev. Control, 50, pp. 373-393; Scharbarg, E., Moog, C.H., Mauduit, N., Califano, C., From the hospital scale to nationwide: Observability and identification of models for the COVID-19 epidemic waves (2020) Annu. Rev. Control, , https://doi.org/10.1016/j.arcontrol.2020.09.007, in press; Brugnano, L., Iavernaro, F., Zanzottera, P., A multiregional extension of the sir model, with application to the COVID-19 spread in Italy (2020) Math. Method. Appl. Sci.; Ansumali, S., Kaushal, S., Kumar, A., Prakash, M.K., Vidyasagar, M., Modelling a pandemic with asymptomatic patients, impact of lockdown and herd immunity, with applications to sars-cov-2 (2020) Annu. Rev. Control, , https://doi.org/10.1016/j.arcontrol.2020.10.003, in press; Gatto, M., Bertuzzo, E., Mari, L., Miccoli, S., Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures (2020) Proc. Nat. Acad. Sci., 117 (19), pp. 10484-10491; Scarabaggio, P., Carli, R., Cavone, G., Epicoco, N., Dotoli, M., (2021) Stochastic Non-pharmaceutical Optimal Control Strategies to Mitigate COVID-19, , https://doi.org/10.36227/techrxiv.14413259.v1, TechRxiv preprint; Google COVID-19 Community Mobility Reports, , www.google.com/covid19/mobility, Google LLC, Accessed: 2021-01-14; Bai, Y., Yao, L., Wei, T., Tian, F., Presumed asymptomatic carrier transmission of COVID-19 (2020) JAMA, 323 (14), pp. 1406-1407; The Civil Protection Department, , http://www.protezionecivile.gov.it/, Accessed: 2021-01-14; Hu, H., Nigmatulina, K., Eckhoff, P., The scaling of contact rates with population density for the infectious disease models (2013) Math. Biosci., 244 (2), pp. 125-134; Santamaria, C., Sermi, F., Spyratos, S., Iacus, S.M., Measuring the impact of COVID-19 confinement measures on human mobility using mobile positioning data. A european regional analysis (2020) Saf. Sci., 132, p. 104925; Iacus, S.M., Santamaria, C., Sermi, F., Spyratos, S., Tarchi, D., Vespe, M., Human mobility and COVID-19 initial dynamics (2020) Nonlinear Dynamics, 101 (3), pp. 1901-1919; Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Clinical characteristics of coronavirus disease 2019 in China (2020) N. Engl. J. Med., 382 (18), pp. 1708-1720; Li, Q., Guan, X., Wu, P., Wang, X., Early transmission dynamics in Wuhan, China, of novel coronavirus. infected pneumonia (2020) N. Engl. J. Med.; Pedersen, M., Meneghini, M., (2020) Quantifying Undetected COVID-19 Cases and Effects of Containment Measures in Italy: Predicting Phase 2 Dynamics, , 03; Ehmann, K.Z., Drosten, C., Wendtner, C., Zange, M., Virological assessment of hospitalized cases of coronavirus disease 2019 (2020) Nature, 581, pp. 465-469; Liu, Y., Yan, L.-M., Wan, L., Xiang, T.-X., Viral dynamics in mild and severe cases of COVID-19 (2020) Lancet Inf. Dis.; Bertozzi, A.L., Franco, E., Mohler, G., Short, M.B., Sledge, D., The challenges of modeling and forecasting the spread of COVID-19 (2020) Proc. Nat. Acad. Sci., 117 (29), pp. 16732-16738; COVID-19: Indicazioni per la Durata e Il Termine della Quarantena, , http://www.salute.gov.it/portale/home.html, Accessed: 2021-01-14; Wei, C., Wang, Z., Liang, Z., Liu, Q., The focus and timing of COVID-19 pandemic control measures under healthcare resource constraints (2020) MedRxiv; Lemos-Paiao, A.P., Silva, C.J., Torres, D.F., A new compartmental epidemiological model for COVID-19 with a case study of Portugal (2020) Ecol. Complex., p. 100885; Giordano, G., Blanchini, F., Bruno, R., Colaneri, P., Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy (2020) Nat. Med., 26, pp. 855-860; Zhou, F., Yu, T., Du, R., Fan, G., Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study (2020) Lancet; Aspelund, K., Droste, M., Stock, J.H., Walker, C.D., Identification and estimation of undetected COVID-19 cases using testing data from Iceland (2020) NBER Work. Pap. No. w27528; Decision & Control Laboratory, , http://dclab.poliba.it/covid-19, Accessed: 2021-04-27},
    document_type={Conference Paper},
    source={Scopus},
    }

2020

  • 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, G. and Epicoco, N. and Dotoli, M.},
    title={Process re-engineering based on colored petri nets: The case of an Italian textile company},
    journal={2020 28th Mediterranean Conference on Control and Automation, MED 2020},
    year={2020},
    pages={856-861},
    doi={10.1109/MED48518.2020.9182937},
    art_number={9182937},
    note={cited By 0},
    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},
    references={Dooley, L., O'Sullivan, D., Decision support system for the management of systems change (1999) Technovation, 19 (8), pp. 483-493; Bhaskar, H., Singh, R., Business process reengineering: A recent review (2014) Global Journal of Business Management, 8 (2), pp. 24-51; Dassisti, M., Hy-change: A hybrid methodology for continuous performance improvement of manufacturing processes (2010) Int. J. Prod. Res., 48 (15), pp. 4397-4422; Nan, X., Li, A., You, J., Modeling and analysis of business process reengineering of manufacturing system (2008) 4th Int. Conf. Wireless Communications, Networking and Mobile Computing, pp. 1-4; Madushela, N., Pretorius, J.C., An integrated approach to business process reengineering management (2017) Proc. World Congress on Engineering 2017, 2, pp. 1-5; School, H.B., (2010) Improving Business Processes: Expert Solutions to Everyday Challenges, , Harvard Business Review Press; Ghanadbashi, S., Ramsin, R., Towards a method engineering approach for business process reengineering (2016) Iet Software, 10 (2), pp. 27-44; Guimaraes, T., Paranjape, K., Testing success factors for manufacturing bpr project phases (2013) Int. J. Adv. Manuf. Tech., 68 (9-12), pp. 1937-1947; Falcone, D., Di Bona, G., Silvestri, A., Forcina, A., Belfiore, G., Petrillo, A., An integrated model for an advanced production process-agile re-engineering project management (2018) IFAC-PapersOnLine, 51 (11), pp. 1630-1635; Vaez-Alaei, M., Baboli, A., Tavakkoli-Moghaddam, R., A new approach to integrate resilience engineering and business process reengineering design (2018) 2018 Ieee Int. Conf. Industrial Engineering and Engineering Management. Ieee, pp. 778-782; Dotoli, M., Epicoco, N., Falagario, M., Costantino, N., Turchiano, B., An integrated approach for warehouse analysis and optimization: A case study (2015) Comput. Ind., 70, pp. 56-69; Garcés, E.M., Mafla, G., Reyes, F., Analysis, review and development of a conceptual model, based on class diagrams as a component of uml, focused on industrial automation (2019) Int. J. Control Syst. and Robot., 4, pp. 6-10; Serrano Lasa, I., Ochoa Laburu, C., De Castro, V.R., An evaluation of the value stream mapping tool (2008) Business Process Management Journal, 14 (1), pp. 39-52; Dotoli, M., Epicoco, N., Falagario, M., Cavone, G., A timed petri nets model for intermodal freight transport terminals (2014) Ifac Proceedings Volumes, 47 (2), pp. 176-181; Aguilar-Saven, R.S., Business process modelling: Review and framework (2004) Int. J. Prod. Econ., 90 (2), pp. 129-149; Cavone, G., Dotoli, M., Epicoco, N., Seatzu, C., Intermodal terminal planning by petri nets and data envelopment analysis (2017) Control Eng. Pract., 69, pp. 9-22; Cavone, G., Dotoli, M., Epicoco, N., Franceschelli, M., Seatzu, C., Hybrid petri nets to re-design low-automated production processes: The case study of a sardinian bakery (2018) IFAC-PapersOnLine, 52 (7), pp. 265-270; Jensen, K., Monographs in theoretical computer science (1997) Coloured Petri Nets-Basic Concepts, 1. , Analysis Methods and Practical Use. Springer-Verlag; https://dreamprojectspa.it/en/, Dream Project accessed: 2020-04-28; Law, A., Kelton, W., (2010) Simulation Modeling and Analysis, , McGraw-Hill},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, P. and Carli, R. and Cavone, G. and Dotoli, M.},
    title={Smart control strategies for primary frequency regulation through electric vehicles: A battery degradation perspective},
    journal={Energies},
    year={2020},
    volume={13},
    number={17},
    doi={10.3390/en13174586},
    art_number={4586},
    note={cited By 6},
    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},
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Lett, 3, p. e161; Boenzi, F., Digiesi, S., Facchini, F., Mossa, G., Mummolo, G., Sustainable warehouse logistics: A NIP model for non-road vehicles and storage configuration selection (2015) Proceedings of the XX Summer School Operational Excellence Experience “Francesco Turco”, , Naples, Italy, 16-18 September; Casalino, G., Del Buono, N., Mencar, C., Nonnegative matrix factorizations for intelligent data analysis (2016) Non-Negative Matrix Factorization Techniques, pp. 49-74. , Springer: Berlin/Heidelberg, Germany; D'Amato, G., Avitabile, G., Coviello, G., Talarico, C., DDS-PLL phase shifter architectures for phased arrays: Theory and techniques (2019) IEEE Access, 7, pp. 19461-19470; Kotb, A.O., Shen, Y.C., Zhu, X., Huang, Y., iParker-A new smart car-parking system based on dynamic resource allocation and pricing (2016) IEEE Trans. Intell. Transp. Syst, 17, pp. 2637-2647; Hosseini, S.S., Badri, A., Parvania, M., The plug-in electric vehicles for power system applications: The vehicle to grid (V2G) concept (2012) Proceedings of the 2012 IEEE International Energy Conference and Exhibition (ENERGYCON), pp. 1101-1106. , Florence, Italy, 9-12 September IEEE: Piscataway, NJ, USA, 2012; Galus, M.D., Koch, S., Andersson, G., Provision of load frequency control by PHEVs, controllable loads, and a cogeneration unit (2011) IEEE Trans. Ind. Electron, 58, pp. 4568-4582; Datta, U., Kalam, A., Shi, J., Battery Energy Storage System for Aggregated Inertia-Droop Control and a Novel Frequency Dependent State-of-Charge Recovery (2020) Energies, 13, p. 2003; Kempton, W., Udo, V., Huber, K., Komara, K., Letendre, S., Baker, S., Brunner, D., Pearre, N., A test of vehicle-to-grid (V2G) for energy storage and frequency regulation in the PJM system (2008) Results Ind. Univ. Res. 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Sci, 7, p. 308; Tchagang, A., Yoo, Y., V2B/V2G on Energy Cost and Battery Degradation under Different Driving Scenarios, Peak Shaving, and Frequency Regulations (2020) World Electr. Veh. J, 11, p. 14; Baure, G., Dubarry, M., Durability and Reliability of EV Batteries under Electric Utility Grid Operations: Impact of Frequency Regulation Usage on Cell Degradation (2020) Energies, 13, p. 2494; Stroe, D.I., Lærke, R., Stan, A.I., Kjær, P.C., Teodorescu, R., Kær, S.K., Field experience from Li-ion BESS delivering primary frequency regulation in the Danish energy market (2014) Ecs Trans, 61, p. 1. , Swierczy nski, M; Stroe, D.I., Knap, V., Swierczynski, M., Stroe, A.I., Teodorescu, R., Operation of a grid-connected lithium-ion battery energy storage system for primary frequency regulation: A battery lifetime perspective (2016) IEEE Trans. Ind. Appl, 53, pp. 430-438; Han, S., Han, S., Economic feasibility of V2G frequency regulation in consideration of battery wear (2013) Energies, 6, pp. 748-765; Kundur, P., Balu, N.J., Lauby, M.G., (1994) Power System Stability and Control, 7. , McGraw-Hill: New York, NY, USA; Maheshwari, A., Paterakis, N.G., Santarelli, M., Gibescu, M., Optimizing the operation of energy storage using a non-linear lithium-ion battery degradation model (2020) Appl. Energy, 261, p. 114360; Yan, G., Liu, D., Li, J., Mu, G., A cost accounting method of the Li-ion battery energy storage system for frequency regulation considering the effect of life degradation (2018) Prot. Control Mod. Power Syst, 3, pp. 1-9; Yan, G., Zhu, X., Li, J., Mu, G., Luo, W., Yang, K., Control strategy design for hybrid energy storage system with intrinsic operation life measurement and calculation (2013) Dianli Xitong Zidonghua Automation Electr. Power Syst, 37, pp. 110-114},
    document_type={Article},
    source={Scopus},
    }
  • 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, R. and Cavone, G. and Pippia, T. and Schutter, B.D. and Dotoli, M.},
    title={A Robust MPC Energy Scheduling Strategy for Multi-Carrier Microgrids},
    journal={IEEE International Conference on Automation Science and Engineering},
    year={2020},
    volume={2020-August},
    pages={152-158},
    doi={10.1109/CASE48305.2020.9216875},
    art_number={9216875},
    note={cited By 3},
    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},
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    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, G. and Dotoli, M. and Epicoco, N. and Morelli, D. and Seatzu, C.},
    title={Design of Modern Supply Chain Networks Using Fuzzy Bargaining Game and Data Envelopment Analysis},
    journal={IEEE Transactions on Automation Science and Engineering},
    year={2020},
    volume={17},
    number={3},
    pages={1221-1236},
    doi={10.1109/TASE.2020.2977452},
    art_number={9040428},
    note={cited By 5},
    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},
    references={Choi, T.-M., Supply chain systems coordination with multiple risk sensitive retail buyers (2016) IEEE Trans. Syst., Man, Cybern., Syst., 46 (5), pp. 636-645. , May; Zhou, Y., Gong, D.-C., Huang, B., Peters, B.A., The impacts of carbon tariff on green supply chain design (2017) IEEE Trans. Autom. Sci. Eng., 14 (3), pp. 1542-1555. , Jul; Dias, L.S., Ierapetritou, M.G., From process control to supply chain management: An overview of integrated decision making strategies (2017) Comput. Chem. Eng., 106, pp. 826-835. , Nov; Guo, Y., Hu, F., Allaoui, H., Boulaksil, Y., A distributed approximation approach for solving the sustainable supply chain network design problem (2018) Int. J. Prod. Res., 57 (11), pp. 3695-3718. , Dec; Dubey, R., Gunasekaran, A., Childe, S.J., Papadopoulos, T., Blome, C., Luo, Z., Antecedents of resilient supply chains: An empirical study (2019) IEEE Trans. Eng. Manag., 66 (1), pp. 8-19. , Feb; Dotoli, M., Epicoco, N., Falagario, M., Integrated supplier selection and order allocation under uncertainty in agile supply chains (2015) Proc. IEEE 20th Conf. Emerg. Technol. Factory Autom. (ETFA), pp. 1-6. , Sep; Matopoulos, A., Barros, A.C., Vorst Der Van J. A., J.G., Resource-efficient supply chains: A research framework, literature review and research agenda (2015) Supply Chain Manage., Int. J., 20 (2), pp. 218-236. , Mar; Dotoli, M., Epicoco, N., Falagario, M., A fuzzy technique for supply chain network design with quantity discounts (2016) Int. J. Prod. Res., 55 (7), pp. 1862-1884. , Apr; Dotoli, M., Epicoco, N., Integrated network design of agile resource-efficient supply chains under uncertainty IEEE Trans. Syst., Man, Cybern., Syst, , to be published; Cavone, G., Dotoli, M., Epicoco, N., Morelli, D., Seatzu, C., A game-theoretical design technique for multi-stage supply chains under uncertainty (2018) Proc. IEEE 14th Int. Conf. Autom. Sci. Eng. (CASE), pp. 528-533. , Aug; Govindan, K., Fattahi, M., Keyvanshokooh, E., Supply chain network design under uncertainty: A comprehensive review and future research directions (2017) Eur. J. Oper. Res., 263 (1), pp. 108-141. , Nov; Kumar, D., Rahman, Z., Chan, F.T.S., A fuzzy AHP and fuzzy multi-objective linear programming model for order allocation in a sustainable supply chain: A case study (2016) Int. J. Comput. Integr. Manuf., 30 (6), pp. 535-551. , Feb; Srivathsan, S., Kamath, M., An analytical performance modeling approach for supply chain networks (2012) IEEE Trans. Autom. Sci. Eng., 9 (2), pp. 265-275. , Apr; Benjaafar, S., Li, Y., Daskin, M., Carbon footprint and the management of supply chains: Insights from simple models (2013) IEEE Trans. Autom. Sci. Eng., 10 (1), pp. 99-116. , Jan; Dotoli, M., Epicoco, N., Falagario, M., Sciancalepore, F., A cross-efficiency fuzzy data envelopment analysis technique for performance evaluation of decision making units under uncertainty (2015) Comput. Ind. Eng., 79, pp. 103-114. , Jan; Sevilla, N.C., Padon, M.L.A., Cabusas, K.G.L., Ocampo, L.A., Abad, G.K.M., Recent approaches to supplier selection: A review of literature within 2006-2016 (2018) Int. J. Integr. Supply Manage., 12 (1-2), p. 22; Tsao, Y.-C., Zhang, Q., Zeng, Q., Supply chain network design considering RFID adoption (2017) IEEE Trans. Autom. Sci. Eng., 14 (2), pp. 977-983. , Apr; Alikhani, R., Torabi, S.A., Altay, N., Strategic supplier selection under sustainability and risk criteria (2019) Int. J. Prod. Econ., 208, pp. 69-82. , Feb; Lima-Junior, F.R., Carpinetti, L.C.R., Quantitative models for supply chain performance evaluation: A literature review (2017) Comput. Ind. Eng., 113, pp. 333-346. , Nov; Dotoli, M., Epicoco, N., Falagario, M., Sciancalepore, F., A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty (2015) Int. Trans. Oper. Res., 23 (4), pp. 725-748. , Feb; Salwa, C.H., Ramanan, T.R., Development of a sustainable strategic marketing model for self-help groups-An analytical hierarchical approach (2017) Int. J. Services Oper. Manage., 26 (3), pp. 318-331; Soheilirad, S., Govindan, K., Mardani, A., Zavadskas, E.K., Nilashi, M., Zakuan, N., Application of data envelopment analysis models in supply chain management: A systematic review and meta-analysis (2017) Ann. Oper. Res., 271 (2), pp. 915-969. , Sep; Ghorabaee, M.K., Amiri, M., Zavadskas, E.K., Antucheviciene, J., Supplier evaluation and selection in fuzzy environments: A review of MADM approaches (2017) Econ. Res.-Ekonomska Istraẑivanja, 30 (1), pp. 1073-1118. , May; Simić, D., Kovacević, I., Svircević, V., Simić, S., 50 years of fuzzy set theory and models for supplier assessment and selection: A literature review (2017) J. Appl. Log., 24, pp. 85-96. , Nov; Azadnia, A.H., Saman, M.Z.M., Wong, K.Y., Sustainable supplier selection and order lot-sizing: An integrated multi-objective decision-making process (2014) Int. J. Prod. Res., 53 (2), pp. 383-408. , Jul; Sadic, S., De Sousa, J.P., Crispim, J.A., A two-phase MILP approach to integrate order, customer and manufacturer characteristics into dynamic manufacturing network formation and operational planning (2018) Expert Syst. Appl., 96, pp. 462-478. , Apr; Leider, S., Lovejoy, W.S., Bargaining in supply chains (2016) Manage. Sci., 62 (10), pp. 3039-3058. , Sep; Esmaeili, M., Allameh, G., Tajvidi, T., Using game theory for analysing pricing models in closed-loop supply chain from short-and long-term perspectives (2015) Int. J. Prod. Res., 54 (7), pp. 2152-2169. , Nov; Xu, J., Zhao, S., Noncooperative game-based equilibrium strategy to address the conflict between a construction company and selected suppliers (2017) J. Construct. Eng. Manage., 143 (8). , Aug; Mohammaditabar, D., Ghodsypour, S.H., Hafezalkotob, A., A game theoretic analysis in capacity-constrained supplier-selection and cooperation by considering the total supply chain inventory costs (2016) Int. J. Prod. Econ., 181, pp. 87-97. , Nov; Nagarajan, M., Soŝić, G., Game-theoretic analysis of cooperation among supply chain agents: Review and extensions (2008) Eur. J. Oper. Res., 187 (3), pp. 719-745. , Jun; Leng, M., Parlar, M., Game theoretic applications in supply chain management: A review (2016) Inf. Syst. Oper. Res., 43 (3), pp. 187-220. , May; Zimmermann, H.-J., Fuzzy set theory (2010) Wiley Interdiscipl. Reviews: Comput. Statist., 2 (3), pp. 317-332. , Apr; Charnes, A., Cooper, W.W., Rhodes, E., Measuring the efficiency of decision making units (1978) Eur. J. Oper. Res., 2 (6), pp. 429-444. , Nov; Sexton, T.R., Silkman, R.H., Hogan, A.J., Data envelopment analysis: Critique and extensions (1986) New Directions Program Eval., 1986 (32), pp. 73-105; Garg, D., Narahari, Y., Mechanism design for single leader stack-elberg problems and application to procurement auction design (2008) IEEE Trans. Autom. Sci. Eng., 5 (3), pp. 377-393. , Jul},
    document_type={Article},
    source={Scopus},
    }
  • 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, G. and Montaruli, V. and Van Den Boom, T.J.J. and Dotoli, M.},
    title={Demand-Oriented Rescheduling of Railway Traffic in Case of Delays},
    journal={7th International Conference on Control, Decision and Information Technologies, CoDIT 2020},
    year={2020},
    pages={1040-1045},
    doi={10.1109/CoDIT49905.2020.9263874},
    art_number={9263874},
    note={cited By 0},
    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},
    references={Yin, J., Tang, T., Yang, L., Xun, J., Huang, Y., Gao, Z., Research and development of automatic train operation for railway transportation systems: A survey (2017) Transportation Research Part C: Emerging Technologies, 85, pp. 548-572; Cao, Y., Ma, L., Zhang, Y., Application of fuzzy predictive control technology in automatic train operation (2019) Cluster Computing, 22 (6), pp. 14135-14144; Liang, Y., Liu, H., Qian, C., Wang, G., A modified genetic algorithm for multi-objective optimization on running curve of automatic train operation system using penalty function method (2019) International Journal of Intelligent Transportation Systems Research, 17 (1), pp. 74-87; Cacchiani, V., Huisman, D., Kidd, M., Kroon, L., Toth, P., Veelenturf, L., Wagenaar, J., An overview of recovery models and algorithms for real-time railway rescheduling (2014) Transportation Research Part B: Methodological, 63, pp. 15-37; Cavone, G., Dotoli, M., Epicoco, N., Seatzu, C., A decision making procedure for robust train rescheduling based on mixed integer linear programming and data envelopment analysis (2017) Applied Mathematical Modelling, 52, pp. 255-273; Ghaemi, N., Cats, O., Goverde, R., Railway disruption management challenges and possible solution directions (2017) Public Transport, 9 (1-2), pp. 343-364; Dotoli, M., Epicoco, N., Falagario, M., Turchiano, B., Cavone, G., Convertini, A., A decision support system for real-time rescheduling of railways (2014) 2014 European Control Conference (ECC, pp. 696-701. , ieee; Corman, F., D'Ariano, A., Marra, A., Pacciarelli, D., Samà, M., Integrating train scheduling and delay management in real-time railway traffic control (2017) Transportation Research Part E: Logistics and Transportation Review, 105, pp. 213-239; Josyula, S.P., Krasemann, J.T., Passenger-oriented railway traffic re-scheduling: A review of alternative strategies utilizing passenger flow data (2017) 7th International Conference on Railway Operations Modelling and Analysis, , Lille; Dollevoet, T., Huisman, D., Kroon, L., Schmidt, M., Schöbel, A., Delay management including capacities of stations (2015) Transportation Science, 49 (2), pp. 185-203; Kanai, S., Shiina, K., Harada, S., Tomii, N., An optimal delay management algorithm from passengers' viewpoints considering the whole railway network (2011) Journal of Rail Transport Planning & Management, 1 (1), pp. 25-37; Luan, X., Wang, Y., De Schutter, B., Meng, L., Lodewijks, G., Corman, F., Integration of real-time traffic management and train control for rail networks-part 1: Optimization problems and solution approaches (2018) Transportation Research Part B: Methodological, 115, pp. 41-71; Li, T., Sun, D., Jing, P., Yang, K., Smart card data mining of public transport destination: A literature review (2018) Information, 9 (1), p. 18; Østbø Sørensen, A., Bjelland, J., Bull-Berg, H., Landmark, A.D., Akhtar, M.M., Olsson, N., Use of mobile phone data for analysis of number of train travellers (2018) Journal of Rail Transport Planning & Management, 8 (2), pp. 123-144; Bemporad, A., Morari, M., Control of systems integrating logic, dynamics, and constraints (1999) Automatica, 35 (3), pp. 407-427; Cavone, G., Blenkers, L., Boom Den T.Van, Dotoli, M., Seatzu, C., De Schutter, B., Railway disruption: A bi-level rescheduling algorithm (2019) 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT, pp. 54-59. , ieee; Kersbergen, B., Rudan, J., Boom Den T.Van, De Schutter, B., Towards railway traffic management using switching max-plus-linear systems (2016) Discrete Event Dynamic Systems, 26 (2), pp. 183-223},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, R. and Cavone, G. and Othman, S.B. and Dotoli, M.},
    title={IoT based architecture for model predictive control of HVAC systems in smart buildings},
    journal={Sensors (Switzerland)},
    year={2020},
    volume={20},
    number={3},
    doi={10.3390/s20030781},
    art_number={781},
    note={cited By 27},
    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},
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Environ., 51, pp. 388-394; Klaučo, M., Drgoňa, J., Kvasnica, M., Di Cairano, S., Building temperature control by simple mpc-like feedback laws learned from closed-loop data (2014) IFAC Proc, 47, pp. 581-586; Klaučo, M., Kvasnica, M., Explicit MPC approach to PMV-based thermal comfort control (2014) Proceeding of the 53Rd IEEE Conference on Decision and Control (CDC), pp. 4856-4861. , Los Angeles, CA, USA; (2005) ISO 7730: Ergonomics of the Thermal Environment—Analytical Determination and Interpretation of Thermal Comfort Using Calculation of the PMV and PPD Indices and Local Thermal Comfort Criteria, p. 60. , ISO: Geneva, Switzerland; Fanger, P.O., (1970) Thermal Comfort: Analysis and Application in Environment Engineering, p. 244. , Danish Technical Press: Copenhagen, Denmark; Shaikh, P.H., Nor, N.B.M., Nallagownden, P., Elamvazuthi, I., Ibrahim, T., A review on optimized control systems for building energy and comfort management of smart sustainable buildings (2014) Renew. Sustain. 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Simu., 6, pp. 159-174; Ascione, F., Bianco, N., de Stasio, C., Mauro, G.M., Vanoli, G.P., Simulation-based model predictive control by the multi-objective optimization of building energy performance and thermal comfort (2016) Energy Build, 111, pp. 131-144; Carli, R., Cavone, G., Dotoli, M., Epicoco, N., Scarabaggio, P., Model predictive control for thermal comfort optimization in building energy management systems (2019) Proceeding of the 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 2608-2613. , Bari, Italy, 6–9 October; Ramanathan, B., Vittal, V., A Framework for Evaluation of Advanced Direct Load Control With Minimum Disruption (2008) IEEE Trans. Power Syst., 23, pp. 1681-1688; ASHRAE Handbook: HVAC Systems and Equipment (1996) American Society of Heating, Refrigerating, and Air Conditioning Engineers, pp. 1-10. , Atlanta, GA, USA; Rode, C., Peuhkuri, R.H., Mortensen, L.H., Hansen, K.K., Time, B., Gustavsen, A., Ojanen, T., Arfvidsson, J., Moisture Buffering of Building Materials; BYG DTU-126 Report (2005) Department of Civil Engineering, Technical University of Denmark: Lyngby, Denmark, , https://backend.orbit.dtu.dk/ws/portalfiles/portal/2415500/byg-r126.pdf; Srinivas, J., (2004) Compr. Handbook of Mechanical Engineering, , Laxmi Publication: New Delhi, India; Murray, F.W., (1966) On the Computation of Saturation Vapor Pressure, , Technical Report; Rand Corp.: Santa Monica, CA, USA; Pippia, T., Sijs, J., de Schutter, B., A Parametrized Model Predictive Control Approach for Microgrids (2018) Proceeding of the IEEE Conference on Decision and Control, pp. 3171-3176. , Miami, FL, USA; García, C.E., Prett, D.M., Morari, M., Model predictive control: Theory and practice-A survey (1989) Automatica, 25, pp. 335-348; (2019) Beeta Home Page, , https://www.beeta.it/en/; Singh, M., Rajan, M.A., Shivraj, V.L., Balamuralidhar, P., Secure MQTT for Internet of Things (IoT (2015) Proceeding of the 2015 5Th International Conference on Communication Systems and Network Technologies (CSNT), pp. 746-751. , Gwalior, India},
    document_type={Article},
    source={Scopus},
    }
  • Cavone, G., van den Boom, T., Blenkers, L., Dotoli, M., Seatzu, C. & De Schutter, B. (2020) An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks. IN IEEE Transactions on Automation Science and Engineering, .. 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. IEEE
    @ARTICLE{Cavone2020,
    author={Cavone, G. and van den Boom, T. and Blenkers, L. and Dotoli, M. and Seatzu, C. and De Schutter, B.},
    title={An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks},
    journal={IEEE Transactions on Automation Science and Engineering},
    year={2020},
    doi={10.1109/TASE.2020.3040940},
    note={cited By 1},
    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. IEEE},
    author_keywords={Delays; Feedback control; Heuristic algorithms; Mixed Integer Linear (MIL) Programming (MILP); Model Predictive Control (MPC); Optimization; Prediction algorithms; Rail transportation; railway traffic disruption; Real-time systems; 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},
    document_type={Article},
    source={Scopus},
    }
  • 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, R. and Cavone, G. and Epicoco, N. and Scarabaggio, P. and Dotoli, M.},
    title={Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario},
    journal={Annual Reviews in Control},
    year={2020},
    volume={50},
    pages={373-393},
    doi={10.1016/j.arcontrol.2020.09.005},
    note={cited By 19},
    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},
    references={Alleman, T., Torfs, E., Nopens, I., COVID-19: From model prediction to model predictive control (2020) https://biomath. ugent. be/sites/default/files/2020-04/Alleman_etal_v2. pdf, accessed April, 30, p. 2020; Bai, Y., Yao, L., Wei, T., Tian, F., Jin, D.-Y., Chen, L., Wang, M., Presumed asymptomatic carrier transmission of covid-19 (2020) Jama, 323 (14), pp. 1406-1407; Bertozzi, A.L., Franco, E., Mohler, G., Short, M.B., Sledge, D., The challenges of modeling and forecasting the spread of covid-19 (2020) arXiv preprint arXiv:2004.04741; Bin, M., Cheung, P., Crisostomi, E., Ferraro, P., Myant, C., Parisini, T., Shorten, R., On fast multi-shot epidemic interventions for post lock-down mitigation: Implications for simple covid-19 models (2020) arXiv preprint arXiv:2003.09930; Bin, M., Cheung, P., Crisostomi, E., Ferraro, P., Myant, C., Parisini, T., Shorten, R., On fast multi-shot epidemic interventions for post lock-down mitigation: Implications for simple covid-19 models (2020) arXiv preprint arXiv:2003.09930; Brugnano, L., Iavernaro, F., Zanzottera, P., A multiregional extension of the SIR model, with application to the COVID-19 spread in Italy (2020) Mathematical Methods in the Applied Sciences, , Wiley Online Library; Bussell, E.H., Dangerfield, C.E., Gilligan, C.A., Cunniffe, N.J., Applying optimal control theory to complex epidemiological models to inform real-world disease management (2019) Philosophical Transactions of the Royal Society B, 374 (1776), p. 20180284; Calafiore, G.C., Novara, C., Possieri, C., A modified SIR model for the COVID-19 contagion in Italy (2020) arXiv preprint arXiv:2003.14391; Carli, R., Cavone, G., Dotoli, M., Epicoco, N., Scarabaggio, P., Model predictive control for thermal comfort optimization in building energy management systems (2019) 2019 ieee international conference on systems, man and cybernetics (smc), pp. 2608-2613. , IEEE; Casella, F., Can the COVID-19 epidemic be controlled on the basis of daily test reports? (2021) IEEE Control Systems Letters, 5 (3), pp. 1079-1084; Chen, Z., Discrete-time vs. continuous-time epidemic models in networks (2019) IEEE Access, 7, pp. 127669-127677; Della Rossa, F., Salzano, D., Di Meglio, A., Intermittent yet coordinated regional strategies can alleviate the COVID-19 epidemic: A network model of the Italian case (2020) arXiv preprint arXiv:2005.07594; Di Domenico, L., Pullano, G., Coletti, P., Hens, N., Colizza, V., Expected impact of school closure and telework to mitigate COVID-19 epidemic in France (2020) Technical Report, , Report; Ferguson, N., Laydon, D., Nedjati-Gilani, G., Imai, N., Ainslie, K., Baguelin, M., Cuomo-Dannenburg, G., Report 9: Impact of non-pharmaceutical interventions (npis) to reduce covid19 mortality and healthcare demand (2020) Imperial College London, 10, p. 77482; (2020), https://www.gazzettaufficiale.it/eli/id/2020/04/27/20A02352/sg, Gazzetta Ufficiale Repubblica Italiana, Decree of the President of the Council of Ministers april 26, 2020: urgent measures regarding the containment and management of the COVID-19 epidemiological emergency (in Italian) [Online; accessed 26. Aug. 2020]; Gatto, M., Bertuzzo, E., Mari, L., Miccoli, S., Carraro, L., Casagrandi, R., Rinaldo, A., Spread and dynamics of the covid-19 epidemic in italy: Effects of emergency containment measures (2020) Proceedings of the National Academy of Sciences, 117 (19), pp. 10484-10491; Giordano, G., Blanchini, F., Bruno, R., Colaneri, P., Di Filippo, A., Di Matteo, A., Colaneri, M., Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy (2020) Nature Medicine, pp. 1-6; Hernandez-Vargas, E.A., Alanis, A.Y., Tetteh, J., A new view of multiscale stochastic impulsive systems for modeling and control of epidemics (2019) Annual Reviews in Control, 48, pp. 242-249; Hethcote, H.W., The mathematics of infectious diseases (2000) SIAM Review, 42, pp. 599-653; Hu, H., Nigmatulina, K., Eckhoff, P., The scaling of contact rates with population density for the infectious disease models (2013) Mathematical biosciences, 244 (2), pp. 125-134; (2020), http://www.salute.gov.it, Italian Ministry of Health, The Italian Ministry of Health website., Accessed: 2020-08-13; (2020), https://www.istat.it/en/information-and-services, Italian Statistics National Institute, The Italian National Institute of Statistics website. 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Natick, Massachusetts; Mei, W., Mohagheghi, S., Zampieri, S., Bullo, F., On the dynamics of deterministic epidemic propagation over networks (2017) Annual Reviews in Control, 44, pp. 116-128; Morato, M.M., Normey-Rico, J.E., Sename, O., Model predictive control design for linear parameter varying systems: A survey (2020) Annual Reviews in Control; Ngonghala, C.N., Iboi, E., Eikenberry, S., Scotch, M., MacIntyre, C.R., Bonds, M.H., Gumel, A.B., Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel coronavirus (2020) Mathematical Biosciences, p. 108364; Nowzari, C., Preciado, V.M., Pappas, G.J., Analysis and control of epidemics: A survey of spreading processes on complex networks (2016) IEEE Control Systems Magazine, 36 (1), pp. 26-46; Rachah, A., Torres, D.F., Mathematical modelling, simulation, and optimal control of the 2014 ebola outbreak in west africa (2015) Discrete Dynamics in Nature and Society, 2015; Ridenhour, B., Kowalik, J.M., Shay, D.K., Unraveling r 0: Considerations for public health applications (2018) American journal of public health, 108 (S6), pp. S445-S454; Rodrigues, H.S., Monteiro, M.T.T., Torres, D.F., Vaccination models and optimal control strategies to dengue (2014) Mathematical biosciences, 247, pp. 1-12; Google, L.L.C., (2020), http://www.google.com/covid19/mobility, Google COVID-19 Community Mobility Reports., Accessed: 2020-08-13; Sélley, F., Besenyei, Á., Kiss, I.Z., Simon, P.L., Dynamic control of modern, network-based epidemic models (2015) SIAM Journal on applied dynamical systems, 14 (1), pp. 168-187; Silva, C.J., Torres, D.F., Optimal control for a tuberculosis model with reinfection and post-exposure interventions (2013) Mathematical Biosciences, 244 (2), pp. 154-164; Watkins, N.J., Nowzari, C., Pappas, G.J., Robust economic model predictive control of continuous-time epidemic processes (2019) IEEE Transactions on Automatic Control, 65 (3), pp. 1116-1131; Zhao, S., Chen, H., Modeling the epidemic dynamics and control of COVID-19 outbreak in China (2020) Quantitative Biology, 8, pp. 11-19; (2020), https://www.who.int/emergencies/diseases/novel-coronavirus-2019, World Health Organization, Coronavirus disease (COVID-19) pandemic, Accessed: 2020-08-13},
    document_type={Article},
    source={Scopus},
    }
  • 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, R. and Cavone, G. and Epicoco, N. and Di Ferdinando, M. and Scarabaggio, P. and Dotoli, M.},
    title={Consensus-Based Algorithms for Controlling Swarms of Unmanned Aerial Vehicles},
    journal={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
    year={2020},
    volume={12338 LNCS},
    pages={84-99},
    doi={10.1007/978-3-030-61746-2_7},
    note={cited By 3},
    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},
    references={Bandala, A., Dadios, E., Vicerra, R., Lim, L.G., Swarming algorithm for unmanned aerial vehicle (UAV) quadrotors: Swarm behavior for aggregation, foraging, formation, and tracking (2014) J. Adv. Comput. Intell. Intell. Inform., 18 (5), pp. 745-751; Barabasi, A.L., Taming complexity (2005) Nat. Phys., 1 (2), pp. 68-70; Colorado, J., Barrientos, A., Martinez, A., Lafaverges, B., Valente, J., Mini-quadrotor attitude control based on Hybrid Backstepping & Frenet-Serret theory (2010) Proceedings of the IEEE International Conference on Robotics and Automation (ICRA); Dong, X., Yu, B., Shi, Z., Zhong, Y., Time-varying formation control for unmanned aerial vehicles: Theories and applications (2015) IEEE Trans. Contr. Syst. Techn., 23 (1), pp. 340-348; Dong, X., Zhou, Y., Ren, Z., Zhong, Y., Time-varying formation tracking for second-order multi-agent systems subjected to switching topologies with application to quadrotor formation flying (2016) IEEE Trans. Ind. Electron., 64 (6), pp. 5014-5024; Gazi, V., Passino, K., (2011) Swarm Stability and Optimization, , https://doi.org/10.1007/978-3-642-18041-5, Springer, Heidelberg; Gioioso, G., Franchi, A., Salvietti, G., Scheggi, S., Prattichizzo, D., The flying hand: A formation of UAVs for cooperative aerial telemanipulation (2014) Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 4335-4341; Gu, Z., Shi, P., Yue, D., Ding, Z., Decentralized adaptive event-triggered h∞ filtering for a class of networked nonlinear interconnected systems (2018) IEEE Trans. Cybern., 49 (5), pp. 1570-1579; Indu, C., Singh, R., Trajectory planning and optimization for UAV communication: A review (2020) J. Discret. Math. Sci. Cryptog., 23 (2), pp. 475-483; Kushleyev, A., Mellinger, D., Powers, C., Kumar, V., Towards a swarm of agile micro quadrotors (2013) Auton. Robots, 35 (4), pp. 287-300; Lee, H., Kim, H., Kim, H., Path planning and control of multiple aerial manipulators for a cooperative transportation (2015) Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); Low, C., A dynamic virtual structure formation control for fixedwing UAVs (2011) Proceedings of the 9Th IEEE IEEE International Conference on Control and Automation (ICCA), pp. 627-632. , pp; Magnussen, O., Ottestad, M., Hovland, G., Experimental validation of a quaternion-based attitude estimation with direct input to a quadcopter control system (2013) Proceedings of the International Conference on Unmanned Aircraft Systems Unmanned Aircraft Systems (ICUAS); Mellinger, D., Michael, N., Kumar, V., Trajectory generation and control for precise aggressive maneuvers with quadrotors (2014) Exp. Robot., 79, pp. 361-373; Monteiro, S., Bicho, E., A dynamical systems approach to behavior-based formation control (2002) Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 2606-2611. , pp; Mu, B., Shi, Y., Distributed LQR consensus control for heterogeneous multia-gent systems: Theory and experiments (2018) IEEE/ASME Trans. Mech., 23 (1), pp. 434-443; Nathan, P., Almurib, H., Kumar, T., A review of autonomous multi-agent quadrotor control techniques and applications (2011) Proceedings of 4Th International Conference on Mechatronics (ICOM); Pantelimon, G., Tepe, K., Carriveau, R., Ahmed, S., Survey of multi-agent communication strategies for information exchange and mission control of drone deployments (2019) J. Intell. Robot. Syst., 95, pp. 779-788; Ren, W., Beard, R., (2008) Distributed Consensus in Multi-Vehicle Cooperative Control-Theory and Applications, , https://doi.org/10.1007/978-1-84800-015-5, Springer, London; Roldo, V., Cunha, R., Cabecinhas, D., Silvestre, C., Oliveira, P., A leader-following trajectory generator with application to quadrotor formation flight (2014) Robot. Auton. Syst., 62 (10), pp. 1597-1609; Sa, I., Corke, P., Estimation and control for an open-source quadcopter (2011) Australian Conference of Robotics and Automation (ACRA; Saska, M., Autonomous deployment of swarms of micro-aerial vehicles in cooperative surveillance (2014) Proceedings of the International Conference on Unmanned Aircraft Systems (ICUAS); Saska, M., Vakula, J., Preucil, L., Swarms of micro aerial vehicles stabilized under a visual relative localization (2014) Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 3570-3575. , pp; Seo, J., Ahn, C., Kim, Y., Controller design for UAV formation flight using consensus based decentralized approach (2009) Proceedings of the AIAA Infotech@Aerospace Conference; Song, Z., Duan, C., Wang, J., Wu, Q., Chattering-free full-order recursive sliding mode control for finite-time attitude synchronization of rigid spacecraft (2019) J. Franklin Inst., 356 (2), pp. 998-1020; Toksoz, M., Oguz, S., Gazi, V., Decentralized formation control of a swarm of quadrotor helicopters (2019) Proceedings of the IEEE 15Th International Conference on Control and Automation (ICCA); Wang, C., Tnunay, H., Zuo, Z., Lennox, B., Ding, Z., Fixed-time formation control of multirobot systems: Design and experiments (2019) IEEE Trans. Ind. Electron., 66 (8), pp. 6292-6301; Wang, C., Zuo, Z., Qi, Z., Ding, Z., Predictor-based extended-state-observer design for consensus of MASs with delays and disturbances (2009) IEEE Trans. Cybern., 49 (4), pp. 1259-1269; Wang, J., Zhou, Z., Wang, C., Shan, J., Multiple quadrotors formation flying control design and experimental verification (2019) Unmanned Syst, 7 (1), pp. 47-54; Zhao, S., Affine formation maneuver control of multi-agent systems (2018) IEEE Trans. Autom. Contr., 63 (12), pp. 4140-4155; Zhao, S., Dimarogonas, D., Sun, Z., Bauso, D., A general approach to coordination control of mobile agents with motion constraints (2018) IEEE Trans. Automat. Contr., 63 (5), pp. 1509-1516},
    document_type={Conference Paper},
    source={Scopus},
    }

2019

  • 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, R. and Cavone, G. and Dotoli, M. and Epicoco, N. and Manganiello, C. and Tricarico, L.},
    title={ICT-based methodologies for sheet metal forming design: A survey on simulation approaches},
    journal={Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
    year={2019},
    volume={2019-October},
    pages={128-133},
    doi={10.1109/SMC.2019.8914082},
    art_number={8914082},
    note={cited By 0},
    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},
    references={Suchy, I., (2006) Handbook of Die Design, , McGraw-Hill; Vollertsen, F., Schmidt, F., Dry metal forming: Definition, chances and challenges (2014) Int. J. Precis. Eng. Manuf. Technol, 1 (1), pp. 59-62; Mulidrán, P., Spišák, E., Majerníková, J., Springback prediction in sheet metal forming via fea simulation (2017) Int. J. Eng. Sci, 6 (9), pp. 49-52; Geiger, M., Merklein, M., Kerausch, M., Finite element simulation of deep drawing of tailored heat treated blanks (2004) CIRP Ann, 53 (1), pp. 223-226; Ingarao, G., Di Lorenzo, R., Design of complex sheet metal forming processes: A new computer aided progressive approach (2010) Int. J. Mater. Form, 3 (1), pp. 21-24; (1998) Schuler GmbH., Metal Forming Handbook, , Springer Berlin Heidelberg; Ramezani, M., Ripin, Z.M., Forming of shallow parts using rubber tools (2012) Rubber-Pad Form. Process, pp. 65-102; Reddy, P., Reddy, G., Prasad, P., A review on finite element simulations in metal forming (2012) Int. J. Mod. Eng. Res, 2 (4), pp. 2326-2330; Zhou, D., Knowledge based cloud fe simulation of sheet metal forming processes (2016) J. Vis. Exp, 118; LS-DYNA, , www.ansys.com/en-gb/products/structures/ansys-ls-dyna, [Accessed: 18-Apr-2019]; AutoForm, , www.autoform.com/en/products/solution-overview, [Accessed: 18-Apr-2019]; Abaqus, , www.3ds.com/products-services/simulia/products/abaqus, [Accessed: 18-Apr-2019]; Pam-Stamp, , www.esi.com.au/software/pamstamp, [Accessed: 18-Apr-2019]; DeGarmo, E.P., Black, J.T., Kohser, R.A., (2017) Materials and Processes in Manufacturing, , Wiley; Ashby, M.F., Shercliff, H., Cebon, D., (2018) Materials: Engineering, Science, Processing and Design, , Elsevier; Iorio, L., Strano, M., Monno, M., Development of a die compensation algorithm for sheet metal stamping with deformable tools (2015) Proc. ASME 2015 International Manufacturing Science and Engineering Conference; Vrolijk, M., Ogawa, T., Camanho, A., Biasutti, M., Lorenz, D., A study with esi pam-stamp® on the influence of tool deformation on final part quality during a forming process (2018) AIP Conference Proceedings, 1960 (1); Cafolla, J., Hall, R.W., Norman, D.P., McGregor, J., Forming to crash' simulation in full vehicle models (2003) 4th European LS-DYNA Users Conference; Wang, W.R., Chen, G.L., Lin, Z.Q., Li, S.H., Determination of optimal blank holder force trajectories for segmented binders of step rectangle box using pid closed-loop fem simulation (2007) Int. J. Adv. Manuf. Technol, 32 (11-12), pp. 1074-1082; Wang, Y., Liu, D.-Z., Li, R., Numerical investigation for the flexible stretch-stamp forming process of sheet metal (2019) Adv. Mech. Eng, 11 (1), pp. 1-11; Slota, J., Jurišin, M., Springback prediction in sheet metal forming processes (2012) J. Technol. Plast, 37 (1), pp. 93-103; Mulidrán, P., Šiser, M., Slota, J., Spišák, E., Sleziak, T., Numerical prediction of forming car body parts with emphasis on springback (2018) Metals, 8 (6); Strano, M., Optimization under uncertainty of sheet-metal-forming processes by the finite element method (2006) Proc. Inst. Mech. Eng. Part B J. Eng. Manuf, 220 (8), pp. 1305-1315; Shaikh, A.M.G., Rao, T.B., Sheet metal forming simulations for heavy commercial vehicle parts by ls-dyna (2013) Glob. J. Res. Eng. Automot. Eng, 13 (1), pp. 35-40; Koreek, D., Solfronk, P., Sobotka, J., Kolnerová, M., Determination the influence of load-rate on strain and spring-back magnitude for titanium alloy by means of numerical simulation (2019) Manuf. Technol, 19 (1), pp. 82-88; Hochholdinger, B., Grass, H., Lipp, A., Hora, P., Determination of flow curves by stack compression tests and inverse analysis for the simulation of hot forming (2009) 7th European LS-DYNA Conference; Papadakis, L., Schober, A., Zaeh, M.F., Considering manufacturing effects in automotive structural crashworthiness: A simulation chaining approach (2013) Int. J. Crashworthiness, 18 (3), pp. 276-287; Jadhav, S., Schoiswohl, M., Buchmayr, B., Applications of finite element simulation in the development of advanced sheet metal forming processes (2018) BHM Berg-und Hüttenmännische Monatshefte, 163 (3), pp. 109-118; Mohamed, M., Norman, D., Petre, A., Melotti, F., Szegda, D., Advances in fem simulation of hfq® aa6082 tailor welded blanks for automotive applications (2018) IOP Conf. Ser. Mater. Sci. Eng, 418 (1), pp. 1-8; Karbasian, H., Tekkaya, A.E., A review on hot stamping (2010) J. Mater. Process. Technol, 210, pp. 2103-2118; Kuhn, H., Medlin, D., (2000) Mechanical Testing and Evaluation, , ASM International; Mosterman, P.J., Zander, J., Industry 4. 0 as a cyber-physical system study (2016) Softw. Syst. Model, 15 (1), pp. 17-29},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, R. and Cavone, G. and Dotoli, M. and Epicoco, N. and Scarabaggio, P.},
    title={Model predictive control for thermal comfort optimization in building energy management systems},
    journal={Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
    year={2019},
    volume={2019-October},
    pages={2608-2613},
    doi={10.1109/SMC.2019.8914489},
    art_number={8914489},
    note={cited By 7},
    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},
    references={Dean, B.P., Dulac, J., Petrichenko, K., Graham, Towards a zeroemission, efficient, and resilient buildings and construction sector (2016) Global Status Report; Ranieri, L., Mossa, G., Pellegrino, R., Digiesi, S., Energy recovery from the organic fraction of municipal solid waste: A real optionsbased facility assessment (2018) Sustain, 10 (2), p. 368. , Jan; Jouhara, H., Yang, J., Energy efficient hvac systems (2018) Energy and Buildings, 179, pp. 83-85; Piccinni, G., Avitabile, G., Coviello, G., Talarico, C., Distributed amplifier design for UWB positioning systems using the gm over id methodology (2016) 2016 13th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2016; Shaikh, P.H., Nor, N.B.M., Nallagownden, P., Elamvazuthi, I., Ibrahim, T., A review on optimized control systems for building energy and comfort management of smart sustainable buildings (2014) Renewable and Sustainable Energy Reviews, 34, pp. 409-429; Ma, Y., Borrelli, F., Hencey, B., Coffey, B., Bengea, S., Haves, P., Model predictive control for the operation of building cooling systems (2012) IEEE Trans. Control Syst. Technol, 20 (3), pp. 796-803; Serale, G., Fiorentini, M., Capozzoli, A., Bernardini, D., Bemporad, A., Model predictive control (mpc) for enhancing building and hvac system energy efficiency: Problem formulation, applications and opportunities (2018) Energies, 11 (3); Hazyuk, I., Ghiaus, C., Penhouet, D., Optimal temperature control of intermittently heated buildings using model predictive control: Part II-control algorithm (2012) Build. Environ, 51, pp. 388-394; Klauo, M., Drgoa, J., Kvasnica, M., Di Cairano, S., Building temperature control by simple mpc-like feedback laws learned from closed-loop data (2014) IFAC Proceedings Volumes (IFACPapersOnline), 19, pp. 581-586; Klauco, M., Kvasnica, M., Explicit mpc approach to pmv-based thermal comfort control (2014) Proceedings of the IEEE Conference on Decision and Control, pp. 4856-4861. , 2015-Febru February; (2005) ISO 7730: Ergonomics of the Thermal Environment-Analytical Determination and Interpretation of Thermal Comfort Using Calculation of the PMV and PPD Indices and Local Thermal Comfort Criteria, p. 60. , International Organization for Standardization, ISO Stand; Fanger, P.O., (1970) Thermal Comfort: Analysis and Application in Environment Engineering; Afram, A., Janabi-Sharifi, F., Theory and applications of hvac control systems-a review of model predictive control (mpc) (2014) Building and Environment, 72; Xu, Z., Hu, G., Spanos, C.J., Schiavon, S., Pmv-based eventtriggered mechanism for building energy management under uncertainties (2017) Energy Build, 152, pp. 73-85; West, S.R., Ward, J.K., Wall, J., Trial results from a model predictive control and optimisation system for commercial building hvac (2014) Energy Build, 72, pp. 271-279; Alamin, Y.I., Del Mar Castilla, M., Álvarez, J.D., Ruano, A., An economic model-based predictive control to manage the users' thermal comfort in a building (2017) Energies, 10 (3); Cigler, J., Prívara, S., Váa, Z., Žáeková, E., Ferkl, L., Optimization of predicted mean vote index within model predictive control framework: Computationally tractable solution (2012) Energy Build, 52, pp. 39-49. , Sep; Corbin, C.D., Henze, G.P., May-Ostendorp, P., A model predictive control optimization environment for real-time commercial building application (2013) J. Build. Perform. Simul, 6 (3), pp. 159-174; Ascione, F., Bianco, N., De Stasio, C., Mauro, G.M., Vanoli, G.P., Simulation-based model predictive control by the multi-objective optimization of building energy performance and thermal comfort (2016) Energy Build, 111, pp. 131-144; Pippia, T., Sijs, J., De Schutter, B., A parametrized model predictive control approach for microgrids (2019) Proceedings of the IEEE Conference on Decision and Control, pp. 3171-3176. , 2018-Decem; García, C.E., Prett, D.M., Morari, M., Model predictive control: Theory and practice-a survey (1989) Automatica, 25 (3), pp. 335-348; Farina, M., Betti, G., Scattolini, R., A solution to the tracking problem using distributed predictive control (2018) 2013 European Control Conference (ECC), pp. 4347-4352; Beeta, , https://www.beeta.it/en/, [Accessed: 24-Apr-2019]; Node-RED : User Guide, , https://nodered.org/docs/user-guide/, [Accessed: 24-Apr-2019]; Singh, M., Rajan, M.A., Shivraj, V.L., Balamuralidhar, P., Secure mqtt for internet of things (iot) (2015) Proceedings-2015 5th International Conference on Communication Systems and Network Technologies, CSNT 2015, pp. 746-751},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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},
    journal={2019 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019},
    year={2019},
    pages={54-59},
    doi={10.1109/CoDIT.2019.8820380},
    art_number={8820380},
    note={cited By 5},
    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},
    references={Dotoli, M., Epicoco, N., Falagario, M., Turchiano, B., Cavone, G., Convertini, A., A decision support system for real-time rescheduling of railways (2014) 2014 European Control Conference, pp. 696-701; Cavone, G., Dotoli, M., Epicoco, N., Seatzu, C., Intermodal terminal planning by petri nets and data envelopment analysis (2017) Control Eng. Pract., 69, pp. 9-22; Kersbergen, B., Van Den Boom, T., De Schutter, B., Distributed model predictive control for railway traffic management (2016) Transp. Res. Part C Emerg. Technol., 68, pp. 462-489. , Jul; Li, X., Shou, B., Ralescu, D., Train rescheduling with stochastic recovery time: A new track-backup approach (2014) IEEE Trans. Syst. Man, Cybern. Syst., 44 (9), pp. 1216-1233. , Sep; Cacchiani, V., An overview of recovery models and algorithms for real-time railway rescheduling (2014) Transp. Res. Part B: Methodological, 63, pp. 15-37. , Pergamon. May; Dollevoet, T., Huisman, D., Kroon, L.G., Veelenturf, L.P., Wagenaar, J.C., Application of an iterative framework for real-time railway rescheduling (2017) Comput. Oper. Res., 78, pp. 203-217. , Feb; Fang, W., Yang, S., Yao, X., A survey on problem models and solution approaches to rescheduling in railway networks (2015) IEEE Trans. On Intell. Transp. Sys., 16 (6), pp. 2997-3016. , Dec; Jacobs, J., Reducing delays by means of computer-aided 'on-the-spot' rescheduling (2004) Adv. Transp., 15, pp. 603-612. , May; Pellegrini, P., Marliere, G., Pesenti, R., Rodriguez, J., Recifemilp: An effective milp-based heuristic for the real-time railway traffic management problem (2015) IEEE Trans. Intell. Transp. Syst., 16 (5), pp. 2609-2619. , Oct; Pellegrini, P., Marlière, G., Rodriguez, J., Real time railway traffic management modeling track-circuits (2012) OpenAccess Ser. Informatics, 25, pp. 23-34. , Jan; Törnquist, J., Persson, J.A., N-tracked railway traffic re-scheduling during disturbances (2007) Transp. Res. Part B Methodol., 41 (3), pp. 342-362. , Mar; Törnquist, J., Computer-based decision support for railway traffic scheduling and dispatching: A review of models and algorithms (2006) Algorithmic MeThods Model. Optim. Rail-ways, 2, p. 23p; Narayanaswami, S., Rangaraj, N., Modelling disruptions and resolving conflicts optimally in a railway schedule (2013) Comput. Ind. Eng., 64 (1), pp. 469-481. , Jan; Ghaemi, N., Cats, O., Goverde, R.M.P., A microscopic model for optimal train short-turnings during complete blockages (2017) Transp. Res. Part B Methodol., 105, pp. 423-437. , Nov; Blenkers, L.L., Van Den Boom, J.T.J., Kersbergen, B., An exploratory study on railway disruption management using switching max-plus linear models (2017) Rail Lille-7th International Conference on Railway Operations Modelling and Analysis, pp. 334-352},
    document_type={Conference Paper},
    source={Scopus},
    }

2018

  • 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, G. and Dotoli, M. and Epicoco, N. and Morelli, D. and Seatzu, C.},
    title={A Game-theoretical Design Technique for Multi-stage Supply Chains under Uncertainty},
    journal={IEEE International Conference on Automation Science and Engineering},
    year={2018},
    volume={2018-August},
    pages={528-533},
    doi={10.1109/COASE.2018.8560501},
    art_number={8560501},
    note={cited By 4},
    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},
    references={Esmaeili, M., Allameh, G., Tajvidi, T., Using game theory for analysing pricing models in closed-loop Supply Chain from short-and long-term perspectives (2016) Int. J. Prod. Res., 54 (7), pp. 2152-2169; Dubey, R., Gunasekaran, A., Childe, S.J., Papadopoulos, T., Blome, C., Luo, Z., Antecedents of resilient supply chains: An empirical study (2017) IEEE Transactions on Engineering Management, , In press; Dias, L.S., Ierapetritou, M.G., From process control to Supply Chain Management: An overview of integrated decision making strategies (2017) Comput. Chem. Eng., 106, pp. 826-835; Dotoli, M., Epicoco, N., Falagario, M., A fuzzy technique for supply chain network design with quantity discounts (2017) Int. J. Prod. Res., 55 (7), pp. 1862-1884; Karsak, E.E., Dursun, M., Taxonomy and review of nondeterministic analytical methods for supplier selection (2016) Int. J. Comput. Integr. Manuf., 29 (3), pp. 263-286; Mukherjee, K., Supplier selection criteria and methods: Past, present and future (2016) Int. J. Oper. Res., 27 (1-2), pp. 356-373; Simi, D., Kovaevi, I., Svirevi, V., Simi, S., 50 years of fuzzy set theory and models for supplier assessment and selection: A literature review (2017) J. Appl. Log., 24, pp. 85-96; Olesen, O.B., Petersen, N.C., Stochastic data envelopment analysis-a review (2016) Eur. J. Oper. Res., 251 (1), pp. 2-21; Dotoli, M., Epicoco, N., Falagario, M., Sciancalepore, F., A stochastic cross-efficiency Data Envelopment Analysis approach for supplier selection under uncertainty (2016) Int. Trans. Oper. Res., 23 (4), pp. 725-748; Govindan, K., Fattahi, M., Keyvanshokooh, E., Supply chain network design under uncertainty: A comprehensive review and future research directions (2017) Eur. J. Oper. Res., 263 (1), pp. 108-141; Leider, S., Lovejoy, W.S., Bargaining in supply chains (2016) Manage. Sci., 62 (10), pp. 3039-3058; Cachon, G.P., Netessine, S., Game theory in supply chain analysis (2004) Handbook of Quantitative Supply Chain Analysis, pp. 13-65; Nagarajan, M., Soši, G., Game-theoretic analysis of cooperation among Supply Chain agents: Review and extensions (2008) Eur. J. Oper. Res., 187 (3), pp. 719-745; Mohammaditabar, D., Ghodsypour, S.H., Hafezalkotob, A., A game theoretic analysis in capacity-constrained supplier-selection and cooperation by considering the total supply chain inventory costs (2016) Int. J. Prod. Econ., 181, pp. 87-97; Leng, M., Parlar, M., Game theoretic applications in Supply Chain Management: A review (2005) INFOR, 43 (3), pp. 187-220; Xu, J., Zhao, S., Noncooperative game-based equilibrium strategy to address the conflict between a construction company and selected suppliers (2017) J. Constr. Eng. Manag., 143 (8), pp. 1-10; Dotoli, M., Epicoco, N., Falagario, M., Sciancalepore, F., A crossefficiency fuzzy data envelopment analysis technique for performance evaluation of decision making units under uncertainty (2015) Comput. Ind. Eng., 79, pp. 103-114; Zimmermann, H.J., Fuzzy set theory (2010) Wiley Interdiscip. Rev. Comput. Stat., 2 (3), pp. 317-332},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, G. and Dotoli, M. and Seatzu, C.},
    title={A Survey on Petri Net Models for Freight Logistics and Transportation Systems},
    journal={IEEE Transactions on Intelligent Transportation Systems},
    year={2018},
    volume={19},
    number={6},
    pages={1795-1813},
    doi={10.1109/TITS.2017.2737788},
    note={cited By 30},
    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},
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    document_type={Article},
    source={Scopus},
    }
  • 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, G. and Dotoli, M. and Epicoco, N. and Seatzu, C.},
    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},
    note={cited By 2},
    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},
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    document_type={Conference Paper},
    source={Scopus},
    }
  • 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},
    note={cited By 13},
    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},
    references={Balduzzi, F., Giua, A., Menga, G., First-order hybrid Petri nets: a model for optimization and control (2015) IEEE Trans. Robot. Autom., 16 (4), pp. 382-399; Basile, F., Carbone, C., Chiacchio, P., Simulation and analysis of discrete-event control systems based on Petri nets using PNetLab (2007) Contr. Eng. Pract., 15 (2), pp. 241-259; Campos, J., Seatzu, C., Xie, X., (2014) Formal methods in manufacturing, , CRC Press; Cavone, G., Dotoli, M., Seatzu, C., Management of Intermodal Freight Terminals by First-Order Hybrid Petri Nets (2016) IEEE Robot. Autom. Lett., 1 (1), pp. 2-9; Choi, J.Y., Reveliotis, S.A., A generalized stochastic Petri net model for performance analysis and control of capacitated reentrant lines (2003) IEEE Trans. Robot. Autom., 19 (3), pp. 474-480; David, R., Alla, H., (2010) Discrete, continuous, and hybrid Petri nets, , Springer Science & Business Media; Dotoli, M., Epicoco, N., Falagario, M., Cavone, C., A Timed Petri Nets model for intermodal freight transport terminals. Proc. 12th IFAC/IEEE Workshop on Discrete Event Systems. In: B. Lennartson et al. (eds) (2014) Discrete Event Systems, 12, pp. 176-181; Dotoli, M., Epicoco, N., Falagario, M., Cavone, G., A Timed Petri Nets model for performance evaluation of intermodal freight transport terminals. (2016) IEEE Trans. Autom. Sci. Eng., 13 (2), pp. 842-857; Hu, H., Zhou, M.C., A Petri Net-based discrete-event control of automated manufacturing systems with assembly operations. (2015) IEEE Trans. Control Syst. Technol., 23 (2), pp. 513-534; Long, F., Zeiler, P., Bertsche, B., (2015) Potentials of coloured Petri nets for realistic availability modelling of production systems in industry 4.0. In Podofillini et al. (eds.), Safety and Reliability of Complex Engineered Systems, pp. 4455-4463. , CRC Press London; Negahban, A., Smith, J.S., Simulation for manufacturing system design and operation: Literature review and analysis. (2014) J. Manuf. Syst., 33, pp. 241-261; Pagani, M.A., Lucisano, M., Mariotti, M., (2014) Italian Bakery Products. In: W. Zhou et al. (eds.), Bakery Products Science and Technology, , John Wiley & Sons, Ltd 2nd ed; Paschino, F., Gambella, F., Giubellino, F., Clemente, F., The level of automation of “carasau” bread production plants. (2007) J. Agric. Eng., 2, pp. 61-64; Pawlewski, P., (2010), Using Petri Nets to model and simulation production systems in process reengineering (case study), In P. Pawlewski (ed.), Petri Nets Applications, InTech, 421-446; Sessego, F., Giua, A., Seatzu, C., (2008) HYPENS: A Matlab tool for timed discrete, continuous and hybrid Petri Nets, Applications and Theory of Petri Nets: Proc. 29th Int. Conf. on Applications and Theory of Petri nets. In: Lect. Notes Comput. Sci., pp. 419-428. , Springer-Verlag 5062; Silva, M., Recalde, L., On fluidification of Petri Nets: from discrete to hybrid and continuous models. (2004) Annual Reviews in Control, 28 (2), pp. 253-266},
    document_type={Conference Paper},
    source={Scopus},
    }

2017

  • 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, G. and Dotoli, M. and Epicoco, N. and Seatzu, C.},
    title={A decision making procedure for robust train rescheduling based on mixed integer linear programming and Data Envelopment Analysis},
    journal={Applied Mathematical Modelling},
    year={2017},
    volume={52},
    pages={255-273},
    doi={10.1016/j.apm.2017.07.030},
    note={cited By 20},
    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},
    references={Castillo, E., Gallego, I., Urena, J.M., Coronado, J.M., Timetabling optimization of a mixed double- and single-tracked railway network (2011) Appl. Math. Model., 35, pp. 859-878; Dotoli, M., Epicoco, N., Falagario, M., Piconese, A., Sciancalepore, F., Turchiano, B., A real-time traffic management model for regional railway network under disturbances (2013) Proceedings of the Ninth International Conference on Automation Science and Engineering, pp. 892-897; Guo, X., Wu, J., Sun, H., Liu, R., Gao, Z., Timetable coordination of first trains in urban railway network: a case study of Beijing (2016) Appl. Math. Model., 40, pp. 8048-8066; Hassannayebi, E., Zegordi, S.H., Yaghini, M., Train timetabling for an urban rail transit line using a Lagrangian relaxation approach (2016) Appl. Math. Model., 40, pp. 9892-9913; Van Aken, S., Bešinović, N., Goverde, R.M., Designing alternative railway timetables under infrastructure maintenance possessions (2017) Transport. Res. B Methodol., 98, pp. 224-238; Li, X., Shou, B., Ralescu, D., Train rescheduling with stochastic recovery time: a new track-backup approach (2014) IEEE Trans. Syst. Man Cybern. Syst., 44 (9), pp. 1216-1233; Cacchiani, V., Huisman, D., Kidd, M., Kroon, L., Toth, P., Veelenturf, L., Wagenaar, J., An Overview of Recovery Models and Algorithms For Real-Time Railway Rescheduling (2013), Econometric Institute Report EI2013-29; Hassannayebi, E., Sajedinejad, A., Mardani, S., Disruption management in urban rail transit system: a simulation based optimization approach (2016) Handbook of Research on Emerging Innovations in Rail Transportation Engineering, pp. 420-450. , IGI Global; Dollevoet, T., Huisman, D., Kroon, L.G., Veelenturf, L.P., Wagenaar, J.C., Application of an iterative framework for real-time railway rescheduling (2017) Comput. Oper. Res., 78, pp. 203-217; Dotoli, M., Epicoco, N., Falagario, M., Turchiano, B., Cavone, G., Convertini, A., A decision support system for real-time rescheduling of railways (2014) Proc. Eur. Control Conf., pp. 696-701; Dotoli, M., Epicoco, N., Falagario, M., Sciancalepore, F., A cross-efficiency fuzzy Data Envelopment Analysis technique for performance evaluation of decision making units under uncertainty (2015) Comput. Ind. Eng., 79, pp. 103-114; Törnquist, J., Computer-based decision support for railway traffic scheduling and dispatching: a review of models and algorithms (2006) Proceedings of the Fifth Workshop on Algorithm Methods Models for Optimization Railways; D'Ariano, A., Innovative decision support system for railway traffic control (2009) Intell. Transp. Syst. Mag., 1, pp. 8-16; Corman, F., Meng, L., A review of online dynamic models and algorithms for railway traffic management (2015) IEEE Trans. Intell. Transp. Syst., 16 (3), pp. 1274-1284; Fang, W., Yang, S., Yao, X., A survey on problem models and solution approaches to rescheduling in railway networks (2015) IEEE Trans. Intell. Transp. Syst., 16 (6), pp. 2997-3016; Xu, X., Li, K., Yang, L., Ye., J., Balanced train timetabling on a single-line railway with optimized velocity (2014) Appl. Math. Model., 38, pp. 894-909; Gao, Y., Yang, L., Li., S., Uncertain models on railway transportation planning problem (2016) Appl. Math. Model., 40, pp. 4921-4934; Andersson, E.V., Peterson, A., Törnquist, J.K., Quantifying railway timetable robustness in critical points (2013) J. Rail Transp. Plan. Manag., 3 (3), pp. 95-110; Salido, M.A., Barber, F., Ingolotti, L., Robustness for a single railway line: analytical and simulation methods (2012) Exp. Syst. Appl., 39, pp. 13305-13327; Hassannayebi, E., Zegordi, S.H., Amin-Naseri, M.R., Yaghini, M., Train timetabling at rapid rail transit lines: a robust multi-objective stochastic programming approach (2017) Oper. Res., 17 (2), pp. 435-477; Dewilde, T., Sels, P., Cattrysse, D., Vansteenwegen, P., Defining robustness of a railway timetable (2011) Proceedings of the Fourth International Seminar on Railway Operational Modelling and Analysis, pp. 1-20. , RailRome; Kroon, L.G., Huisman, D., Maróti, G., Optimisation models for railway timetabling (2008) Railway Timetable and Traffic, , I. Hansen J. Pachl Eurailpress Hamburg; D'Ariano, A., Pacciarelli, D., Pranzo, M., Assessment of flexible timetables in real-time traffic management of a railway bottleneck (2008) Transp. Res. C Emer., 16 (2), pp. 232-245; Kroon, L.G., Dekker, R., Vromans, M.J., Cyclic Railway timetabling: A stochastic Optimization Approach (2007), pp. 41-66. , Springer Berlin Heidelberg; Salido, M.A., Barber, F., Ingolotti, L., Robustness in railway transportation scheduling (2008) Proceedings of the Intelligent Control Automation Conference, pp. 2880-2885; Fischetti, M., Salvagnin, D., Zanette, A., Fast approaches to improve the robustness of a railway timetable (2009) Transp. Sci., 43 (3), pp. 321-335; Liebchen, C., Schachtebeck, M., Schoebel, A., Stiller, S., Prigge, A., Computing delay resistant railway timetables (2010) Comput. Oper. Res., 37 (5), pp. 857-868; Larsen, R., Pranzo, M., D'Ariano, A., Corman, F., Pacciarelli, D., Susceptibility of optimal train schedules to stochastic disturbances of process times (2014) Flex. Serv. Manuf. J., 26 (4), pp. 466-489; Jovanović, P., Kecman, P., Bojović, N., Mandić, D., Optimal allocation of buffer times to increase train schedule robustness (2017) Eur. J. Oper. Res., 256 (1), pp. 44-54; Velasquez, M., Hester, P.T., An analysis of multi-criteria decision making methods (2013) Int. J. Oper. Res., 10 (2), pp. 56-66; Markovits-Somogy, R., Ranking efficient and inefficient decision making units in Data Envelopment Analysis (2011) Int. J. Traffic Transp. Eng., 1 (4), pp. 245-256; Törnquist, J., Persson, A., N-tracked railway traffic re-scheduling during disturbances (2007) Transp. Res. B, 41, pp. 342-362; Adenso-Díaz, B., González, M.O., González-Torre, P., On-line timetable re-scheduling in regional train services (1999) Transp. Res. B, 33 (6), pp. 387-398; Samà, M., Meloni, C., D'Ariano, A., Corman, F., A multi-criteria decision support methodology for real-time train scheduling (2015) J. Rail Transp. Plan. Manag., 5 (3), pp. 146-162; Oneto, L., Fumeo, E., Clerico, G., Canepa, R., Papa, F., Dambra, C., Mazzino, N., Anguita, D., Dynamic delay predictions for large-scale railway networks: deep and shallow extreme learning machines tuned via thresholdout (2017) IEEE Trans. Syst. Man Cybern. Syst., , In press; Hu, X., Cui, N., Demeulemeester, E., Bie, L., Incorporation of activity sensitivity measures into buffer management to manage project schedule risk (2016) Eur. J. Oper. Res., 249 (2), pp. 717-727; Şahin, I., Railway traffic control and train scheduling based on inter-train conflict management (1999) Transp. Res. B, 33, pp. 511-534; Vromans, M.J., Dekker, R., Kroon, L.G., Reliability and heterogeneity of railway services (2006) Eur. J. Oper. Res., 172, pp. 647-665; Zimmermann, H.-J., Fuzzy Set Theory and its Applications (2001), fourth ed. Springer Science & Business Media New York; Jimenez, M., Bilbao, A., Pareto-optimal solution in fuzzy multi-objective linear programming (2009) Fuzzy Sets Syst., 160, pp. 2714-2721},
    document_type={Article},
    source={Scopus},
    }
  • 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, G. and Dotoli, M. and Epicoco, N. and Seatzu, C.},
    title={Intermodal terminal planning by Petri Nets and Data Envelopment Analysis},
    journal={Control Engineering Practice},
    year={2017},
    volume={69},
    pages={9-22},
    doi={10.1016/j.conengprac.2017.08.007},
    note={cited By 13},
    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},
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    document_type={Article},
    source={Scopus},
    }

2016

  • 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, G. and Dotoli, M. and Seatzu, C.},
    title={Resource planning of intermodal terminals using timed Petri nets},
    journal={2016 13th International Workshop on Discrete Event Systems, WODES 2016},
    year={2016},
    pages={44-50},
    doi={10.1109/WODES.2016.7497824},
    art_number={7497824},
    note={cited By 6},
    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},
    references={Dotoli, M., Fanti, M.P., Mangini, A.M., Stecco, G., Ukovich, W., The impact of ICT on intermodal transportation systems: A modelling approach by Petri nets (2010) Contr. Eng. Pract, 18 (8), pp. 893-903; Caris, A., Macharis, C., Janssens, G.K., Decision support in intermodal transport: A new research agenda (2013) Comput. Ind, 64 (2), pp. 105-112; Harris, I., Wang, Y.L., Wang, H.Y., ICT in multimodal transport and technological trends: Unleashing potential for the future (2015) Int. J. Prod. Econ, 159, pp. 88-103; Perego, A., Perotti, S., Mangiaracina, R., ICT for logistics and freight transportation: A literature review and research agenda (2011) Int. J. Phys. Distrib. Logist. Manag, 4 (5), pp. 457-483; Alicke, K., Modeling and optimization of the intermodal terminal Mega Hub (2002) OR Spectrum, 24, pp. 1-17; Boschian, V., Dotoli, M., Fanti, M.P., Iacobellis, G., Ukovich, W., A metamodelling approach to the management of intermodal transportation networks (2011) IEEE Trans. Autom. Sci. Eng, 8 (3), pp. 457-469; Dotoli, M., Fanti, M.P., Iacobellis, G., Mangini, A.M., A first order hybrid Petri net model for supply chain management (2009) IEEE Trans. Autom. Sci. Eng, 6 (4), pp. 744-758; Chen, H., Amodeo, L., Feng, C., Labadi, K., Modeling and performance evaluation of supply chains using batch deterministic and stochastic Petri nets (2005) IEEE Trans. Autom. Sci. Eng, 2 (2), pp. 132-144; Giua, A., Seatzu, C., Modeling and supervisory control of railway networks using Petri nets (2008) IEEE Trans. Autom. Sci. Eng, 5 (3), pp. 431-445; Dotoli, M., Epicoco, N., Falagario, M., Cavone, G., A timed Petri nets model for performance evaluation of intermodal freight transport terminals (2015) IEEE Trans. Aut. Sci. Eng, (99), pp. 1-16. , vol.PP; Liu, C.I., Ioannou, P.A., Petri Net modeling and analysis of automated container terminal using Automated Guided Vehicle systems (2002) Transp. Res. Rec, 1782, pp. 73-83; Dotoli, M., Fanti, M.P., A coloured Petri net model for automated storage and retrieval systems serviced by rail-guided vehicles: A control perspective (2005) Int. J. Comp. Integ. Manuf, 18 (2-3), pp. 122-136; Filipova, K., Stojadinova, T., Hadjiatanasova, V., Application of Petri Nets for transport streams modeling (2002) Facta Universitatis: Architecture and Civil Engineering, 2 (4), pp. 295-306; Silva, C.A., Guedes Soares, C., Signoret, J.P., Intermodal terminal cargo handling simulation using Petri nets with predicates (2014) J. Eng. Marit. Env; Cavone, G., Dotoli, M., Seatzu, C., Management of Intermodal Freight Terminals by First-Order Hybrid Petri Nets (2016) Rob. Aut. Lett, 1 (1), pp. 2-9. , Jan; David, R., Alla, H., (2005) Discrete Continuous, and Hybrid Petri Nets, , Berlin Heidelberg, Springer-Verlag; Zimmermann, A., (2008) Stochastic Discrete Event Systems: Modeling, Evaluation, Applications, , Springer; Law, A.L., (2007) Simulation Modeling & Analysis, , New York: McGraw Hill; Sessego, F., Giua, A., Seatzu, C., HYPENS: A Matlab tool for timed discrete, continuous and hybrid Petri nets (2008) Lecture Notes in Computer Science, 5062, pp. 419-428. , Springer-Verlag},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, M. and Epicoco, N. and Falagario, M. and Cavone, G.},
    title={A Timed Petri Nets Model for Performance Evaluation of Intermodal Freight Transport Terminals},
    journal={IEEE Transactions on Automation Science and Engineering},
    year={2016},
    volume={13},
    number={2},
    pages={842-857},
    doi={10.1109/TASE.2015.2404438},
    art_number={7057695},
    note={cited By 38},
    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},
    references={Alessandri, A., Cervellera, C., Cuneo, M., Gaggero, M., Soncin, G., Modeling and feedback control for resource allocation and performance analysis in container terminals (2008) IEEE Trans. Intell. Transp. Syst., 9 (4), pp. 601-614; Alessandri, A., Cervellera, C., Cuneo, M., Gaggero, M., Soncin, G., Management of logistics operations in intermodal terminals by using dynamic modelling and nonlinear programming (2009) Marit. Econ. Logist., 11 (1), pp. 58-76; Alicke, K., Modeling and optimization of the intermodal terminal Mega Hub (2002) OR Spectrum, 24, pp. 1-17; Baldassarra, A., Impastato, S., Ricci, S., Intermodal terminal simulation for operations management (2010) Eur. Transp., 46, pp. 86-99; Bielli, M., Boulmakoul, A., Rida, M., Object oriented model for container terminal distributed simulation (2006) Eur. J. Oper. Res., 175 (3), pp. 1731-1751; Bontekoning, Y.M., Macharis, C., Trip, J.J., Is a new applied transportation research field emerging? A review of intermodal rail-truck freight transport literature (2004) Transp. Res., 38, pp. 1-34; Boschian, V., Dotoli, M., Fanti, M.P., Iacobellis, G., Ukovich, W., A metamodelling approach to the management of intermodal transportation networks (2011) IEEE Trans. Autom. Sci. Eng., 8 (3), pp. 457-469. , Jul; Caballini, C., Pasquale, C., Sacone, S., Siri, S., An event-triggered receding-horizon scheme for planning rail operations in maritime terminals (2014) IEEE Trans. Intell. Transp. Syst., 15 (1), pp. 365-375; Canonaco, P., Legato, P., Mazza, R.M., Musmanno, R., A queuing network model for the management of berth crane operations (2008) Comput. Oper. Res., 35 (8), pp. 2432-2446; Caris, A., Macharis, C., Janssens, G.K., Planning problems in intermodal freight transport: Accomplishments and prospects (2008) Transport. Plan. Techn., 31 (3), pp. 277-302; Caris, A., Janssens, G.K., Macharis, C., Modelling complex intermodal freight flows (2009) System Complexity to Emergent Properties, Understanding Complex Systems, pp. 291-300. , M. A. Aziz-Alaoui and C. Bertelle, Eds. Berlin, Germany: Springer; Caris, A., Macharis, C., Janssens, G.K., Decision support in intermodal transport: A new research agenda (2013) Comput. Ind., 64 (2), pp. 105-112; Cartení, A., De Luca, S., Tactical and strategic planning for a container terminal: Modelling issues within a discrete event simulation approach (2012) Simul. Modelling Pract. Theory, 21 (1), pp. 123-145; Chen, H., Amodeo, L., Feng, C., Labadi, K., Modeling and performance evaluation of supply chains using batch deterministic and stochastic Petri nets (2005) IEEE Trans. Autom. Sci. Eng., 2 (2), pp. 132-144. , Apr; David, R., Alla, H., (2005) Discrete, Continuous, and Hybrid Petri Nets, , Berlin, Germany: Springer-Verlag; Degano, C., Di Febbraro, A., On using Petri net to detect faulty behaviours in an intermodal container terminal (2002) Proc. 9th Meeting of the Euro Working Group on Transportation, "intermodality, Sustainability and Intelligent Transportation Systems", , Bari, Italy; DeWitt, W., Clinger, J., Intermodal freight transportation (2000) Transportation Research Board-Transportation in the New Millenium: State of the Art; Di Febbraro, A., Porta, G., Sacco, N., A Petri net modelling approach of intermodal terminals based on Metrocargo system (2006) Proc. 9th Intell. Transp. Syst. Conf., pp. 1442-1447. , Toronto, ON, Canada; Dotoli, M., Epicoco, N., Falagario, M., Cavone, G., A timed Petri nets model for intermodal freight transport terminals (2014) Proc. 12th Int. Works. Discr. Event Syst. (WODES'14), pp. 176-181. , Paris-Cachan, France; Dotoli, M., Epicoco, N., Falagario, M., Cavone, G., Turchiano, B., Simulation and performance evaluation of an intermodal terminal using Petri nets (2014) Proc. Int. Conf. Contr., Dec. Inform. Technol. (CoDIT'14), pp. 327-332. , Metz, France; Dotoli, M., Fanti, M.P., A coloured Petri net model for automated storage and retrieval systems serviced by rail-guided vehicles: A control perspective (2005) Int. J. Comp. Integr. Manuf., 18 (2-3), pp. 122-136; Dotoli, M., Fanti, M.P., Iacobellis, G., Mangini, A.M., A first order hybrid Petri net model for supply chain management (2009) IEEE Trans. Autom. Sci. Eng., 6 (4), pp. 744-758. , Oct; Dotoli, M., Fanti, M.P., Mangini, A.M., Stecco, G., Ukovich, W., The impact of ICT on intermodal transportation systems: A modelling approach by Petri nets (2010) Contr. Eng. Pract., 18 (8), pp. 893-903; Dotoli, M., Hammadi, S., Jeribi, K., Russo, C., Zgaya, H., A multiagent decision support system for optimization of co-modal transportation route planning services (2013) Proc. 52nd IEEE Conf. Decision Control, , Florence, Italy; Dotoli, M., Epicoco, N., Falagario, M., Palma, D., Turchiano, B., A train load planning optimization model for intermodal freight transport terminals: A case study (2013) Proc. IEEE Conf. Systems, Man and Cybernetics, , Manchester, U.K; Dotoli, M., Epicoco, N., Falagario, M., Seatzu, C., Turchiano, B., An optimization technique for intermodal rail-road freight transport terminals (2014) Proc. IEEE Int. Conf. Robot. Autom., 6p. , Hong Kong, China; Du, Y., Tan, W., Zhou, M., Timed compatibility analysis of web service composition: A modular approach based on Petri nets (2014) IEEE Trans. Autom. Sci. Eng., 11 (2), pp. 594-606. , Apr; (2011) White Paper on Transport-Roadmap to A Single European Transport Area EU; Filipova, K., Stojadinova, T., Hadjiatanasova, V., Application of Petri Nets for transport streams modeling (2002) Facta Universitatis: Architecture and Civil Engineering, 2 (4), pp. 295-306; Gambardella, L.M., Mastrolilli, M., Rizzoli, A.E., Zaffalon, M., An optimization methodology for intermodal terminal management (2001) J. Intelligent Manufacturing, 12 (5-6), pp. 521-534; Giua, A., DiCesare, F., Silva, M., Generalized Mutual Exclusion Constraints on nets with uncontrollable transitions (1992) Proc. Int. Conf. Syst. Man Cybern., pp. 974-979. , Chicago, IL, USA; Giua, A., Seatzu, C., Modeling and supervisory control of railway networks using Petri nets (2008) IEEE Trans. Autom. Sci. Eng., 5 (3), pp. 431-445. , Jul; Günther, H.O., Kim, K.H., Container terminals and terminal operations (2006) OR Spectrum, 28, pp. 437-445; Harris, I., Wang, Y.L., Wang, H.Y., ICT in multimodal transport and technological trends: Unleashing potential for the future (2015) Int. J. Prod. Econ., 159, pp. 88-103; Kim, W.-S., Kim, J.H., Kim, H., Kwon, H., Morrison, J.R., Capacity and queueing evaluation of port systems with offshore container unloading (2010) Proc. Int. Conf. Logist.Marit. Sys., , Busan, Korea; Law, A.L., (2007) Simulation Modeling & Analysis, , New York, NY, USA: McGraw-Hill; Lee, C., Huang, H.C., Liu, B., Xu, Z., Development of timed Colour Petri net simulation models for air cargo terminal operations (2006) Comput. Ind. Eng., 51 (1), pp. 102-110; Liu, C.I., Ioannou, P.A., Petri Net modeling and analysis of automated container terminal using Automated Guided Vehicle systems (2002) Transp.. Res. Rec., 1782, pp. 73-83; Liu, C.I., Jula, H., Ioannou, P.A., Design, simulation, and evaluation of automated container terminals (2002) IEEE Trans. Intell. Transp. Syst., 3 (1), pp. 12-26. , Mar; Maione, G., Ottomanelli, M., A Petri net model for simulation of container terminal operations (2005) Advanced or and AI Methods in Transportation, pp. 373-378. , A. Jaszkiewicz, Ed. et al. Poznan, Poland: House of Poznan Uni. Technol; Murty, K.G., Liu, J., Wan, Y.W., Linn, R., A decision support system for operations in a container terminal (2005) Decision Supp. Syst., 39 (3), pp. 309-332; Parola, F., Sciomachen, A., Intermodal container flows in a port system network: Analysis of possible growths via simulation models (2005) Int. J. Prod. Econ., 97 (1), pp. 75-88; Perego, A., Perotti, S., Mangiaracina, R., ICT for logistics and freight transportation: A literature review and research agenda (2011) Int. J. Phys. Distrib. Logist. Manag., 4 (5), pp. 457-483; Peterson, J.L., (1981) Petri Net Theory and the Modeling of Systems, , Pearson, Ed. Englewood Cliffs, NJ, USA: Prentice-Hall; Rizzoli, A.E., Fornara, N., Gambardella, L.M., A simulation tool for combined rail/road transport in intermodal terminals (2002) Math. Comput. Simulat., 59 (1-3), pp. 57-71; Sessego, F., Giua, A., Seatzu, C., HYPENS: A Matlab tool for timed discrete, continuous and hybrid Petri nets (2008) Lecture Notes in Computer Science, 5062, pp. 419-428. , Berlin, Germany: Springer-Verlag; Silva, C.A., Soares, C.G., Signoret, J.P., Intermodal terminal cargo handling simulation using Petri nets with predicates (2014) J. Eng. Marit. Env.; Stahlbock, R., Voss, S., Operations research at container terminals: A literature update (2008) OR Spectrum, 30, pp. 1-52; Steenken, D., Voß, S., Stahlbock, R., Container terminal operation and operations research-A classification and literature review (2004) OR Spectrum, 26, pp. 3-49; (2001) Terminology on Combined Transport, , New York and Geneva, United Nations; Vis, I.F.A., De Koster, R.D., Transshipment of containers at a container terminal: An overview (2003) Eur. J. Oper. Res., 147 (1), pp. 1-16; Viswanadham, N., (1999) Analysis of Manufacturing Enterprises: An Approach to Leveraging Value Delivery Processes for Competitive Advantage, , Boston, MA, USA: Kluwer Academic; Zimmermann, A., (2008) Stochastic Discrete Event Systems: Modeling, Evaluation, Applications, , New York, NY, USA: Springer},
    document_type={Article},
    source={Scopus},
    }
  • 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, G. and Dotoli, M. and Seatzu, C.},
    title={Management of Intermodal Freight Terminals by First-Order Hybrid Petri Nets},
    journal={IEEE Robotics and Automation Letters},
    year={2016},
    volume={1},
    number={1},
    pages={2-9},
    doi={10.1109/LRA.2015.2502905},
    art_number={7339445},
    note={cited By 12},
    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},
    references={Harris, I., Wang, Y.L., Wang, H.Y., ICT in multimodal transport and technological trends: Unleashing potential for the future (2015) Int. J. Prod. Econ., 159, pp. 88-103; Boschian, V., Dotoli, M., Fanti, M.P., Iacobellis, G., Ukovich, W., A metamodelling approach to the management of intermodal transportation networks (2011) IEEE Trans. Autom. Sci. Eng., 8 (3), pp. 457-469. , Jul; Dotoli, M., Epicoco, N., Falagario, M., Cavone, G., A timed Petri nets model for performance evaluation of intermodal freight transport terminals (2015) IEEE Trans. Autom. Sci. Eng., pp. 1-16. , Mar; Chen, H., Amodeo, L., Feng, C., Labadi, K., Modeling and performance evaluation of supply chains using batch deterministic and stochastic Petri nets (2005) IEEE Trans. Autom. Sci. Eng., 2 (2), pp. 132-144. , Apr; Dotoli, M., Fanti, M.P., Iacobellis, G., Mangini, A.M., A firstorder hybrid Petri net model for supply chain management (2009) IEEE Trans. Autom. Sci. Eng., 6 (4), pp. 744-758. , Oct; Giua, A., Seatzu, C., Modeling and supervisory control of railway networks using Petri nets (2008) IEEE Trans. Autom. Sci. Eng., 5 (3), pp. 431-445. , Jul; Dotoli, M., Fanti, M.P., Mangini, A.M., Stecco, G., Ukovich, W., The impact of ICT on intermodal transportation systems: A modelling approach by Petri nets (2010) Contr. Eng. Pract., 18 (8), pp. 893-903; Liu, C.I., Ioannou, P.A., Petri net modeling and analysis of automated container terminal using automated guided vehicle systems (2002) Transp. Res. Rec., 1782, pp. 73-83; Dotoli, M., Fanti, M.P., An urban traffic network model via coloured timed Petri nets (2006) Contr. Eng. Pract., 14, pp. 1213-1229; Silva, C.A., Guedes Soares, C., Signoret, J.P., Intermodal terminal cargo handling simulation using Petri nets with predicates (2014) J. Eng. Marit. Environ.; Di Febbraro, A., Giglio, D., Sacco, N., Urban traffic control structure based on hybrid Petri nets (2004) IEEE Trans. Intell. Transp. Syst., 5 (4), pp. 224-237. , Dec; Balduzzi, F., Giua, A., Menga, G., First-order hybrid Petri nets: A model for optimization and control (2000) IEEE Trans. Robot. Autom., 16 (4), pp. 382-399. , Aug; Balduzzi, F., Di Febbraro, A., Combining fault detection and process optimization in manufacturing systems using first-order hybrid Petri nets (2001) Proc. IEEE Int. Conf. Robot. Autom., 1, pp. 40-45; Balduzzi, F., Giua, A., Seatzu, C., Modelling and simulation of manufacturing systems with first-order hybrid Petri nets (2001) Int. J. Prod. Res., 39 (2), pp. 255-282; Kim, Y.W., Inaba, A., Suzuki, T., Okuma, S., Realization of fault tolerant manufacturing system and its scheduling based on hierarchical Petri net modeling (2003) Proc. IEEE Int. Conf. Robot. Autom., 3, pp. 3959-3964; Dotoli, M., Fanti, M.P., Iacobellis, G., A freeway traffic control model by first order hybrid Petri nets (2011) Proc. IEEE Conf. Autom. Sci. Eng., pp. 425-431; Fanti, M.P., Iacobellis, G., Mangini, A.M., Ukovich, W., Freeway traffic modeling and control in a first-order hybrid Petri net framework (2014) IEEE Trans. Autom. Sci. Eng., 11 (1), pp. 90-102. , Jan; Sessego, F., (2008) HYPENS, , http://www.diee.unica.it/automatica/hypens/, [Online]},
    document_type={Article},
    source={Scopus},
    }

2014

  • 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, M. and Epicoco, N. and Falagario, M. and Cavone, G.},
    title={A timed Petri nets model for intermodal freight transport terminals},
    journal={IFAC Proceedings Volumes (IFAC-PapersOnline)},
    year={2014},
    volume={9},
    number={3},
    pages={176-181},
    doi={10.3182/20140514-3-FR-4046.00038},
    note={cited By 10},
    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},
    references={Bevilacqua, V., Costantino, N.N., Dotoli, M., Falagario, M., Sciancalepore, F., Strategic design and multi-objective optimization of distribution networks based on genetic algorithms (2012) Int. J. Comp. Int. Manuf., 25 (12), pp. 1139-1150; Boschian, V., Dotoli, M., Fanti, M.P., Iacobellis, G., Ukovich, W., A metamodelling approach to the management of intermodal transportation networks (2011) IEEE Trans. Aut. Sci. Eng., 8 (3), pp. 457-469; Costantino, N., Dotoli, M., Falagario, M., Fanti, M.P., Mangini, A.M., A model for supply management of agile manufacturing supply chains (2012) Int. J. Prod. Econ., 135 (1), pp. 451-457; David, R., Alla, H., (2005) Discrete, Continuous, and Hybrid Petri Nets, , Berlin Heidelberg: Springer-Verlag; Di Febbraro, A., Porta, G., Sacco, N., A Petri net modelling approach of intermodal terminals based on Metrocargo system (2006) Proc. 9th Intelligent Transportation Systems Conf., pp. 1442-1447. , Toronto (Canada); Dotoli, M., Epicoco, N., Falagario, M., Seatzu, C., Turchiano, B., Optimization of intermodal rail-road freight transport terminals (2014) Proc. IEEE Int. Conf. Rob. Autom. ICRA2014, 6p. , Hong Kong, China; Dotoli, M., Sciancalepore, F., Epicoco, N., Falagario, M., Turchiano, B., Costantino, N., A periodic event scheduling approach for offline timetable optimization of regional railways (2013) Proc. ICNSC2013, 6p. , Paris, France; Dotoli, M., Fanti, M.P., Mangini, A.M., Stecco, G., Ukovich, W., The impact of ICT on intermodal transportation systems: A modelling approach by Petri nets (2010) Control Eng. Pract., 18 (8), pp. 893-903; Eng-Larsson, F., Kohn, C., Modal shift for greener logistics - The shipper's perspective (2012) Int. J. Phys. Distrib. Logist. Manag., 42 (1), pp. 36-59; Fischer, M., Kemper, P., Modeling and analysis of a freight terminal with stochastic Petri nets (2000) Proc. 9th IFAC Symposium Control in Transportation Systems, , Braunschweig (Germany); Giua, A., DiCesare, F., Silva, M., Generalized mutual exclusion constraints on nets with uncontrollable transitions (1992) Proc. 1992 IEEE Int. Conf. Sys. Man Cybern., pp. 974-979. , Chicago (U.S.); Labadi, K., Chen, H., Modelling, analysis and optimisation of supply chains by using Petri net models: The state-of-the-art (2010) Int. J. Business Performance and Supply Chain Modelling, 2 (3-4), pp. 188-215; Perego, A., Perotti, S., Mangiaracina, R., ICT for logistics and freight transportation: A literature review and research agenda (2011) Int. J. Phys. Distrib. Logist. Manag., 41 (5), pp. 457-483; Peterson, J.L., (1981) Petri Net Theory and the Modeling of Systems, , Englewood Cliffs, NJ: Prentice Hall; Sessego, F., Giua, A., Seatzu, C., HYPENS: A Matlab tool for timed discrete, continuous and hybrid Petri nets (2008) Proc. 29th Int. Conf. on Applications and Theory of Petri Nets, pp. 419-428. , Lecture Notes in Computer Science 5062, Springer-Verlag; Viswanadham, N., (1999) Analysis of Manufacturing Enterprises: An Approach to Leveraging Value Delivery Processes for Competitive Advantage, , Boston: Kluwer},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, M. and Epicoco, N. and Cavone, G. and Turchiano, B. and Falagario, M.},
    title={Simulation and performance evaluation of an Intermodal terminal using Petri Nets},
    journal={Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014},
    year={2014},
    pages={327-332},
    doi={10.1109/CoDIT.2014.6996915},
    art_number={6996915},
    note={cited By 3},
    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; Scheduling algorithms; Traffic control, Intermodal freight transport; Intermodal terminals; Intermodal transport; Operational performance; Performance evaluation; Performance indices; Simulation; Timed Petri Net, Discrete event simulation},
    references={Bhattacharya, A., Kumar, S.A., Tiwari, M.K., Talluri, S., An intermodal freight transport system for optimal supply chain logistics (2014) Transportation Research Part C, 38, pp. 73-84; (2001) Terminology on Combined Transport the European Commission (EC), , UN, New York and Geneva; Ferreira, L., Sigut, J., Modelling intermodal freight terminal operations (1995) Road and Transportation Research, 4 (4), pp. 4-16; Maione, G., Discrete-Event dynamic systems modelling distributed multi-agent control of intermodal container terminals (2008) Robotics Automation and Control, pp. 39-58. , Pecherkova P. et al. (eds.); Filipova, K., Stojadinova, T., Hadjiatanasova, V., Application of Petri Nets for transport streams modeling (2002) Facta Universitatis: Architecture and Civil Engineering, 2 (4), pp. 295-306; Labadi, K., Chen, H., Modelling, analysis and optimisation of supply chains by using Petri net models: The state-of-the-art (2010) Int. J. Business Perform. Supply Chain Modelling, 2 (3-4), pp. 188-215; Di Febbraro, A., Porta, G., Sacco, N., A Petri net modelling approach of intermodal terminals based on Metrocargo system (2006) Proc. 9th Intelligent Transportation Systems Conf., pp. 1442-1447. , Toronto (Canada); Dotoli, M., Fanti, M.P., Mangini, A.M., Stecco, G., Ukovich, W., The impact of ICT on intermodal transportation systems: A modelling approach by Petri nets (2010) Contr. Eng. Pract., 18 (8), pp. 893-903; Alicke, K., Modeling and optimization of the intermodal terminal Mega Hub (2002) OR Spectrum, 24, pp. 1-17; Boschian, V., Dotoli, M., Fanti, M.P., Iacobellis, G., Ukovich, W., A metamodelling approach to the management of intermodal transportation networks (2011) IEEE Trans. Autom. Sci. Eng., 8 (3), pp. 457-469; Cassandras, C.G., Lafortune, S., (2008) Introduction to Discrete Event Systems, , 2nd ed., Boston: Kluwer Academic; Peterson, J.L., (1981) Petri Net Theory and the Modeling of Systems, , Englewood Cliffs, NJ: Prentice Hall; Law, A.L., (2007) Simulation Modeling and Analysis, , New York (NY): McGraw-Hill; Viswanadham, N., (1999) Analysis of Manufacturing Enterprises: An Approach to Leveraging Value Delivery Processes for Competitive Advantage, , Boston: Kluwer Academic; Degano, C., Di Febbraro, A., Modelling automated material handling in intermodal terminals (2001) Proc. 2001 IEEWASME Int. Conf. Advanced Intelligent Mechatronics, , 8-12 July, Como, Italy; David, R., Alla, H., (2010) Discrete, Continuous and Hybrid Petri Nets, , Berlinheidelberg: Springer},
    document_type={Conference Paper},
    source={Scopus},
    }
  • 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, M. and Epicoco, N. and Falagario, M. and Turchiano, B. and Cavone, G. and Convertini, A.},
    title={A Decision Support System for real-time rescheduling of railways},
    journal={2014 European Control Conference, ECC 2014},
    year={2014},
    pages={696-701},
    doi={10.1109/ECC.2014.6862177},
    art_number={6862177},
    note={cited By 10},
    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={Artificial intelligence; 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},
    references={Cordeau, J.F., Toth, P., Vigo, D., A survey of optimization models for train routing and scheduling (1998) Transp. Sci., 32, pp. 380-420; Corman, F., D'Ariano, A., Pacciarelli, D., Pranzo, M., Bi-objective conflict detection and resolution in railway traffic management (2012) Transp. Res. C, 20, pp. 79-94; D'Ariano, A., Pranzo, M., Hansen, I.A., Conflict resolution and train speed coordination for solving real-time timetable perturbations (2007) IEEE Trans. Int. Transp. Sys., 8 (2), pp. 208-222; Dotoli, M., Epicoco, N., Falagario, M., Piconese, A., Sciancalepore, F., Turchiano, B., A real time traffic management model for regional railway networks under disturbances (2013) Proc. CASE 2013, , Madison, USA; Dotoli, M., Hammadi, S., Jeribi, K., Russo, C., Zgaya, H., A multi-agent decision support system for optimization of co-modal transportation route planning services (2013) Proc. IEEE CDC2013, , Florence, Italy; Dotoli, M., Sciancalepore, F., Epicoco, N., Falagario, M., Turchiano, B., Costantino, N., A periodic event scheduling approach for offline timetable optimization of regional railways (2013) Proc. ICNSC 2013, , Paris, France; Krasemann, J.T., Design of an effective algorithm for fast response to the re-scheduling of railway traffic during disturbances (2012) Transp. Res., 20, pp. 62-78; Landex, A., Evaluation of railway networks with single track operation using the UIC 406 capacity method (2009) Networks and Spatial Economics, 9 (1), pp. 7-23; Sahin, I., Railway traffic control and train scheduling based on intertrain conflict management (1999) Transp. Res. B, 33, pp. 511-534; Salido, M.A., Barber, F., Ingolotti, L., Robustness in railway transportation scheduling (2008) Proc. Intell. Contr. Autom. Conf., pp. 2880-2885. , Chongqing, China; Törnquist, J., Persson, J.A., N-tracked railway traffic re-scheduling during disturbances (2007) Transp. Res. B, 41, pp. 342-362; Vromans, M.J., Dekker, R., Kroon, L.G., Reliability and heterogeneity of railway services (2006) Eur. J. Op. Res., 172, pp. 647-665},
    document_type={Conference Paper},
    source={Scopus},
    }