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.
翻译:运输部门温室气体排放的增加促使公司和政府提升和支持电动车辆的生产。随着城市化和电子商务的最近发展,运输公司正在用电动车辆取代其常规车队,以加强可持续和环境友好型行动的努力。然而,部署一个EV车队,要求制定高效的路线和补给战略,以缓解其范围有限和降低电池退化率。在这项工作中,考虑建立电动车辆车队,以建设运输和物流能力,电池容量有限,充电站供应量稀少。我们引入了微量电动车辆路线问题(MEVRP),将任何EV的最大距离降到最低,同时考虑为再充电站收费。我们建议一个高效的分支和削减框架以及三阶段混合超常算法,以有效解决各种情况。我们进行了广泛的计算结果和敏感性分析,以证实拟议方法在数量和质量上的效率。