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Multi-objective optimization model for a multi-depot mixed fleet electric vehicle scheduling problem with real-world constraints

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents the problem of public transport planning in terms of the optimal use of the available fleet of vehicles and reductions in operational costs and environmental impact. The research takes into account the large fleet of vehicles of various types that are typically found in large cities, including the increasingly widely used electric buses, many depots, and numerous limitations of urban public transport. The mathematical multi-criteria mathematical model formulated in this work considers many important criteria, including technical, economic, and environmental criteria. The preliminary results of the Mixed Integer Linear Programming solver for the proposed model on both theoretical data and real data from urban public transport show the possibility of the practical application of this solver to the transport problems of medium-sized cities with up to two depots, a heterogeneous fleet of vehicles, and up to about 1500 daily timetable trips. Further research directions have been formulated with regard to larger transport systems and new dedicated heuristic algorithms.
Czasopismo
Rocznik
Strony
137--149
Opis fizyczny
Bibliogr. 24 poz.
Twórcy
autor
  • AGH University of Science and Technology; 30 Mickiewicza Av., 30-059 Kraków, Poland
  • AGH University of Science and Technology, 30 Mickiewicza Av., 30-059 Kraków, Poland
  • AGH University of Science and Technology, 30 Mickiewicza Av., 30-059 Kraków, Poland
autor
  • AGH University of Science and Technology, 30 Mickiewicza Av., 30-059 Kraków, Poland
  • Poznan University of Technology; 5 M. Sklodowska-Curie Square, 60-965 Poznan, Poland
autor
  • Poznan University of Technology; 5 M. Sklodowska-Curie Square, 60-965 Poznan, Poland
  • Cracow University of Technology, 24 Warszawska, 31-155 Krakow, Poland
Bibliografia
  • 1. Bie, Y. & Ji, J. & Wang, X. & Qu, X. Optimization of electric bus scheduling considering stochastic volatilities in trip travel time and energy consumption. Computer-Aided Civil and Infrastructure Engineering. 2021. Vol. 36. No. 12. P. 1530-1548.
  • 2. Bunte, S. & Kliewer, N. An overview on vehicle scheduling models. Public Transport. 2010. Vol. 1. P. 299-317.
  • 3. Ceder, A. Public Transit Planning and Operation: Theory, Modelling and Practice. Oxford: Butterworth-Heinemann, Elsevier Ltd. 2007.
  • 4. Corazza, M.V. & Lizana, P.C. & Pascucci, M. & Petracci, E. & Vasari, D. iGREEN: An integrated emission model for mixed bus fleets. Energies. 2021. Vol. 14. No. 6. Paper. No. 1521.
  • 5. Dirks, N. & Schiffer, M. & Walther, G. On the integration of battery electric buses into urban bus networks. Transportation Research Part C: Emerging Technologies. 2022. Vol. 139. Paper. No. 103628.
  • 6. Ge, L. & Kliewer, N. & Nourmohammadzadeh, A. & Voß, S. & Xie, L. Revisiting the richness of integrated vehicle and crew scheduling. Public Transport. 2022.
  • 7. Gkiotsalitis, K. Bus scheduling considering trip-varying travel times, vehicle availability and capacity. IET Intelligent Transport Systems. 2020. Vol. 14. No 12. P. 1594-1605.
  • 8. Jiang, M. & Zhang, Y. & Zhang, Y. Multi-depot electric bus scheduling considering operational constraint and partial charging: A case study in Shenzhen, China. Sustainability. 2022. Vol. 14. No. 1. Paper. No. 255.
  • 9. Jovanovic, R. & Bayram, I.S. & Bayhan, S. & Voß, S. A GRASP approach for solving large-scale electric bus scheduling problems. Energies. 2021. Vol. 14. No. 20. Paper. No. 6610.
  • 10. Kisielewski, P. Komputerowe wspomaganie planowania komunikacji miejskiej. Warszawa: Wydawnictwo Polifechniki Warszawskiej. 2019. 174 p. [In Polish: Computer-Aided Planning of City Public Transport. Warsaw: Publishing House of Warsaw University of Technology]
  • 11. van Kooten Niekerk, M.E. & van den Akker, J.M. & Hoogeveen, J.A. Scheduling electric vehicles. Public Transport. 2017. Vol. 9. P. 155-176.
  • 12. Li, L. & Lo, H.K. & Feng Xiao, F. Mixed bus fleet scheduling under range and refueling constraints. Transportation Research Part C: Emerging Technologies. 2019. Vol. 104. P. 443-462.
  • 13. Liu, T. & Ceder, A. Research in public transport vehicle scheduling. 2021. Chapter 18. P. 388-408. In: Currie, G. (Ed.). Handbook of Public Transport Research. Cheltenham, UK: Edward Elgar Publishing.
  • 14. Liebchen, C. Periodic Timetable Optimization in Public Transport. Technische Universitat. Disertations, Berlin, 2006.
  • 15. Olsen, N. & Kliewer, N. & Wolbeck, L. A study on flow decomposition methods for scheduling of electric buses in public transport based on aggregated time-space network models. Central European Journal of Operations Research. 2022. Vol. 30. P. 883-919.
  • 16. Pepin, A.S. & Desaulniers, G. & Hertz, A. & Huisman, D. A comparison of five heuristics for the multiple depot vehicle scheduling problem. Journal of Scheduling. 2009. Vol. 12. Paper. No. 17.
  • 17. Perumal, S.S.G. & Dollevoet, T. & Huisman, D. & Lusby, R. & Larsen, J. & Riis, M. Solution approaches for integrated vehicle and crew scheduling with electric buses. Computers & Operations Research. 2021. Vol. 132. Paper. No. 105268.
  • 18. Perumal, S.S.G. & Lusby, R.M. & Larsen, J. Electric bus planning & scheduling: A review of related problems and methodologies. European Journal of Operational Research. 2022. Vol. 301. No. 2. P. 395-413.
  • 19. Reuer, J. & Kliewer, N. & Wolbeck, L. The Electric Vehicle Scheduling Problem. A study on timespace network based and heuristic solution approaches. In: Conference paper CASPT 2015.
  • 20. Schobel, A. Line planning in public transportation: models and methods. OR Spectrum. 2012. Vol. 34. P. 491-510.
  • 21. Yao, E. & Liu, T. & Lu, T. & Yang, Y. Optimization of electric vehicle scheduling with multiple vehicle types in public transport. Sustainable Cities and Society. 2020. Vol. 52. Paper. No. 101862.
  • 22. Wang, J. &Wang, H. & Chang, A. & Song, C. Collaborative optimization of vehicle and crew scheduling for a mixed fleet with electric and conventional buses. Sustainability. 2022. Vol. 14. No. 6. Paper No. 3627.
  • 23. Xu, X. & Ye, Z. & Li, J. & Wang, C. Solving a large-scale multi-depot vehicle scheduling problem in urban bus systems. Mathematical Problems in Engineering. 2018. Vol. 2018. Article ID 4868906. P. 1-13.
  • 24. Zhang, A. & Li, T. & Zheng, Y. & Li, X. & Abdullah, M.G. & Dong, C. Mixed electric bus fleet scheduling problem with partial mixed-route and partial recharging. International Journal of Sustainable Transportation. 2022. Vol. 16. No. 1. P. 73-83.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-51e35c8d-18da-4665-ac7e-318b545c02ae
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