期刊
COMPUTERS & OPERATIONS RESEARCH
卷 76, 期 -, 页码 73-83出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2016.06.013
关键词
Electric vehicles; Vehicle scheduling; Partial charging; Large neighborhood search
类别
资金
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [1234584] Funding Source: National Science Foundation
This paper addresses the Electric Vehicle Scheduling Problem (E-VSP), in which a set of timetabled bus trips, each starting from and ending at specific locations and at specific times, should be carried out by a set of electric buses or vehicles based at a number of depots with limited driving ranges. The electric vehicles are allowed to be recharged fully or partially at any of the given recharging stations. The objective is to firstly minimize the number of vehicles needed to cover all the timetabled trips, and secondly to minimize the total traveling distance, which is equivalent to minimizing the total deadheading distance. A mixed integer programming formulation as well as an Adaptive Large Neighborhood Search (ALNS) heuristic for the E-VSP are presented. ALNS is tested on newly generated E-VSP benchmark instances. Result shows that the proposed heuristic can provide good solutions to large E-VSP instances and optimal or near-optimal solutions to small E-VSP instances. (C) 2016 Elsevier Ltd. All rights reserved.
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