Research on Urban Distribution Path Optimization of Pure Electric Logistics Vehicles Based on Regional Division

In order to solve the problem of time window interruption caused by waste of transportation capacity, rising cost and unreasonable path planning in urban distribution of pure electric logistics vehicles. This study proposes a two-stage optimization method to solve the problem of insufficient power in the middle of distribution due to battery capacity constraints. In the first stage, the K-means clustering algorithm is used to divide the distribution area to reduce the repeated coverage and invalid driving of vehicles. In the second stage, considering the case of midway charging, the path optimization model is constructed with the dual objectives of minimizing the total cost of distribution and minimizing the default rate of time window, and the optimal distribution path is obtained by using the improved genetic algorithm. The two-stage method is applied to the actual scene of Y company’s pure electric logistics vehicle urban distribution, and the total cost of distribution is reduced by 1602.36 yuan, and the time window default rate is reduced by 12.1%. In summary, the two-stage optimization method proposed in this paper significantly improves the time window compliance rate and reduces the cost, and provides a feasible solution for improving the urban distribution efficiency of electric logistics vehicles.