Research on Optimization of E-commerce Express Terminal Distribution Mode
A multi-objective vehicle path optimization model was designed to address the issues of complex vehicle delivery paths and low vehicle utilization in the process of e-commerce express delivery.The model comprehensively considered both the distance traveled by vehicles and the loading rate of vehicles.An improved non-optimal dynamic particle swarm optimization al-gorithm was used to solve the problem,and K-Means clustering was combined to reduce the solution dimension.Improving the learning factor and optimal solution update strategy,the global optimization ability of particle swarm optimization algorithm has been enhanced,and the convergence speed has been accelerated.Finally,the effectiveness of the algorithm was validated using the R101 example from the Solomon dataset.The results indicate that companies can effectively reduce vehicle travel distance,increase vehicle loading rate,and then to improve distribution efficiency and reduce operating costs by reasonably classifying us-ers and then planning vehicle delivery routes.This conclusion can provide theoretical basis and decision support for the innovation of the"last mile"delivery mode in the e-commerce environment.
万方数据
维普
