Abstract
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.
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