Abstract
At present, under the pressure of environmental pollution, logistics enterprises are beginning to use electric vehicles for various distribution services due to their low energy consumption and environmentally friendly nature. Considering the fact that the quality of service and charging strategy have an important impact on the electric vehicle routing problem, to improve the efficiency of electric vehicles in logistics distribution networks, we investigate an electric vehicle routing problem with soft time windows and fast charging (EVRPSTW-FC) stations: mixed integer linear programming is established to minimise total logistics energy consumption. To solve the proposed model, a hybrid adaptive genetic algorithm (HAGA) is proposed. The performance of HAGA is compared and tested with benchmark examples, and the results verify the feasibility and effectiveness of the proposed model and solution algorithm.
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