Optimization of urban unmanned logistics distribution path with multiple distribution centers

Abstract

In addition to the great prospects for development, unmanned distribution has attracted a great deal of social attention as a new type of logistics distribution mode. The use of electric unmanned vehicles for urban logistics distribution can not only reduce enterprise costs but also achieve non-contact distribution and rapid logistics response for unmanned logistics distribution in multiple distribution centers. A multi-distribution center urban unmanned logistics distribution path optimization model is developed for minimizing total cost, taking into account constraints such as battery capacity of electric unmanned vehicles, customer time windows, simultaneous pickup and delivery, and vehicle balance between distribution centers. In this study, an improved genetic algorithm was designed with a reasonable route optimization strategy, and its effectiveness was verified through a variety of calculation examples. Our model was compared with other variant models and parameters. As a result of the analysis, it can be seen that the established model and algorithm can improve the vehicle path and save the distribution costs. This research can promote the development of urban unmanned logistics distribution mode and provide theoretical reference.