Amid increasing environmental concerns, electric vehicles (EVs) are gaining traction as a sustainable transportation alternative. However, the widespread adoption of EVs is hindered by range limitations, inadequate charging infrastructure, and unpredictable access to charging facilities. The battery swapping van (BV) has been proposed as an innovative approach to actively offer on-demand charging at designated locations. This study leverages the novel BV concept and proposes a novel electric vehicle routing model with time windows and en-route mobile battery swapping (EVRPTW-EMBS). This achieves flexible mobile battery swapping services provided by BVs to EVs that are either en route or at customer sites. A tailored heuristic algorithm called CIP-TDP-ILNS is adopted, combining improved large neighborhood search (ILNS) with tree-template dynamic programming (TDP) and cluster-aided integer programming (CIP) to reduce the search space and enhance solving efficiency. Through extensive testing, the CIP-TDP-ILNS algorithm exhibits robust performance, yielding up to 16% cost reductions for the EVRPTW-EMBS compared to the benchmark model. The findings of this study suggest that (1) the EVRPTW-EMBS system is particularly beneficial for servicing clients with wider time windows, and (2) the optimal balance between the quantity of batteries carried and their capacity should be tailored to the logistics network’s size.

中文翻译：

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具有在途移动电池更换功能的电动汽车的交付路线


随着环境问题日益严重，电动汽车 （EV） 作为一种可持续的交通选择越来越受到关注。然而，电动汽车的广泛采用受到续航里程限制、充电基础设施不足和充电设施不可预测的阻碍。电池更换车 （BV） 已被提议作为一种创新方法，在指定地点积极提供按需充电。本研究利用新颖的 BV 概念，提出了一种具有时间窗口和途中移动电池更换 （EVRPTW-EMBS） 的新型电动汽车路径模型。这实现了 BV 为途中或客户现场的电动汽车提供的灵活移动电池更换服务。采用一种称为 CIP-TDP-ILNS 的定制启发式算法，将改进的大邻域搜索 （ILNS） 与树模板动态规划 （TDP） 和集群辅助整数规划 （CIP） 相结合，以减少搜索空间并提高求解效率。通过广泛的测试，CIP-TDP-ILNS 算法表现出强大的性能，与基准模型相比，EVRPTW-EMBS 的成本降低了 16%。这项研究的结果表明，（1） EVRPTW-EMBS 系统特别有利于为时间窗口较宽的客户提供服务，以及 （2） 运输的电池数量与其容量之间的最佳平衡应根据物流网络的规模量身定制。