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
中国国家自然科学基金; 国家重点研发计划;
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
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