A Time-Dependent Electric Vehicle Routing Problem With Congestion Tolls

被引:33
|
作者
Zhang, Ruiyou [1 ]
Guo, Jingmei [1 ]
Wang, Junwei [2 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[2] Univ Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Batteries; Routing; Roads; Electric vehicles; Adaptation models; Time factors; Adaptive large neighborhood search (ALNS); congestion toll; electric vehicle routing problem (EVRP); recharge allocation; time-dependent; LARGE NEIGHBORHOOD SEARCH; MORNING COMMUTE; LOCATION; WINDOWS; ENERGY; IMPACT;
D O I
10.1109/TEM.2019.2959701
中图分类号
F [经济];
学科分类号
02 ;
摘要
Scheduling the recharging of electric vehicle fleets under different scenarios is an important but open problem. One important scenario is that vehicles travel at different speeds in different periods since traffic congestion is common in urban areas nowadays. Therefore, in this article, a novel time-dependent electric vehicle routing problem with congestion tolls is proposed. If a vehicle enters a peak period, a fixed congestion toll needs to be paid in this problem. A mixed integer linear programming model is established and an adaptive large neighborhood search (ALNS) heuristic is designed to solve the model. The model and solving method are validated and evaluated extensively with benchmark instances. Results indicate that a certain level of congestion tolls could prevent vehicles from entering peak periods and relieve road congestions significantly. Furthermore, the ALNS heuristic could provide much better solutions for the problem than typical optimization software, such as Gurobi, in much shorter running time.
引用
收藏
页码:861 / 873
页数:13
相关论文
共 50 条
  • [41] The load-dependent electric vehicle routing problem with time windows
    Wu, Zhiguo
    Wang, Jiepeng
    Chen, Chen
    Liu, Yunhui
    [J]. INTERNATIONAL JOURNAL OF SHIPPING AND TRANSPORT LOGISTICS, 2023, 17 (1-2) : 182 - 213
  • [42] Correction to the Paper "Branch and Price for the Time-Dependent Vehicle Routing Problem with Time Windows"
    Dabia, Said
    Ropke, Stefan
    van Woensel, Tom
    [J]. TRANSPORTATION SCIENCE, 2024, 58 (05)
  • [43] Collaboration and resource sharing in the multidepot time-dependent vehicle routing problem with time windows
    Wang, Yong
    Wei, Zikai
    Luo, Siyu
    Zhou, Jingxin
    Zhen, Lu
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2024, 192
  • [44] A way to optimally solve a green time-dependent vehicle routing problem with time windows
    Iman Kazemian
    Masoud Rabbani
    Hamed Farrokhi-Asl
    [J]. Computational and Applied Mathematics, 2018, 37 : 2766 - 2783
  • [45] The Time-Dependent Vehicle Routing Problem with Time Windows and Road-Network Information
    Ben Ticha H.
    Absi N.
    Feillet D.
    Quilliot A.
    Van Woensel T.
    [J]. Operations Research Forum, 2 (1)
  • [46] Dynamic vehicle routing problem with real-time time-dependent travel times
    Zhao, Xin
    Goncalves, Gilles
    Dupas, Remy
    [J]. 2009 IEEE INTELLIGENT VEHICLES SYMPOSIUM, VOLS 1 AND 2, 2009, : 814 - 819
  • [47] An iterated local search algorithm for the time-dependent vehicle routing problem with time windows
    Hashimoto, Hideki
    Yagiura, Mutsunori
    Ibaraki, Toshihide
    [J]. DISCRETE OPTIMIZATION, 2008, 5 (02) : 434 - 456
  • [48] The time-dependent vehicle routing problem with soft time windows and stochastic travel times
    Tas, Duygu
    Dellaert, Nico
    van Woensel, Tom
    de Kok, Ton
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2014, 48 : 66 - 83
  • [49] An improved multiobjective evolutionary algorithm for time-dependent vehicle routing problem with time windows
    Li, Jia-ke
    Li, Jun-qing
    Xu, Ying
    [J]. Egyptian Informatics Journal, 2024, 28
  • [50] A way to optimally solve a green time-dependent vehicle routing problem with time windows
    Kazemian, Iman
    Rabbani, Masoud
    Farrokhi-Asl, Hamed
    [J]. COMPUTATIONAL & APPLIED MATHEMATICS, 2018, 37 (03): : 2766 - 2783