Electric Vehicle Routing Problem withMobile Battery Swapping Considering Time-Dependent Traffic

For the electric vehicle routing problem with mobile battery swapping considering time-dependent traffic, the impact factors such as time-dependent vehicle speed, customer fuzzy time window and multiple distribution centers are considered, and a mixed integer programming model is established to minimize the sum of the dispatch cost, travel energy consumption cost, customer time window penalty cost and battery wear cost of EV and BSV. Initial solutions are generated by the clusters regarding each customer’s spatio- temporal distance, and a hybrid large neighborhood search algorithm, combining genetic algorithm and large neighborhood search algorithm, is designed. After computing different scales of benchmark instances, this paper verifies the effectiveness of the developed model and algorithm, indicating that the results of this research are conducive to improving the delivery efficiency of logistics enterprises.