论文标题

电动汽车的最小最大路由问题的有效算法

Efficient algorithms for electric vehicles' min-max routing problem

论文作者

Fazeli, Seyed Sajjad, Venkatachalam, Saravanan, Smereka, Jonathon M.

论文摘要

运输部门的温室气体排放量增加,导致公司和政府提升和支持电动汽车的生产(EV)。随着城市化和电子商务方面的最新发展,运输公司正在用电动汽车取代其传统车队,以加强为可持续和环境友好的运营所做的努力。但是,部署EVS机队要求采取有效的路由和充电策略,以减轻其有限的范围并减轻电池降解率。在这项工作中,电动汽车的车队被考虑用于电池容量有限和稀缺充电站的运输和物流功能。我们引入了最小电动汽车路由问题(MEVRP),其中任何EV所传播的最大距离在考虑用于充电站的同时最小化。我们提出了一个有效的分支和切割框架以及可以有效解决各种实例的三相混合启发式算法。进行广泛的计算结果和敏感性分析,以证实拟议方法的效率,无论是定量还是定性。

An increase in greenhouse gases emission from the transportation sector has led companies and the government to elevate and support the production of electric vehicles (EV). With recent developments in urbanization and e-commerce, transportation companies are replacing their conventional fleet with EVs to strengthen the efforts for sustainable and environment-friendly operations. However, deploying a fleet of EVs asks for efficient routing and recharging strategies to alleviate their limited range and mitigate the battery degradation rate. In this work, a fleet of electric vehicles is considered for transportation and logistic capabilities with limited battery capacity and scarce charging station availability. We introduce a min-max electric vehicle routing problem (MEVRP) where the maximum distance traveled by any EV is minimized while considering charging stations for recharging. We propose an efficient branch and cut framework and a three-phase hybrid heuristic algorithm that can efficiently solve a variety of instances. Extensive computational results and sensitivity analyses are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively.

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