Application Research of Factor Constraint Algorithm in E-Commerce Logistics Route Optimization

Abstract

In modern society, e-commerce logistics services are replacing traditional manual transportation methods. However, fresh transportation challenges have emerged. This study proposes applying the factor constraint algorithm to the e-commerce logistics path transportation problem. The multi-objective constraints and optimization of node tasks, vehicle full load, route closure, and other issues in the process of logistics transportation are firstly carried out. The final target is the shortest path of logistics deliver. Then the genetic algorithm, particle swarm algorithm, and ant colony algorithm are integrated to obtain the HMOAC algorithm, and the logistics path transportation model is constructed. The research findings indicate that the HMOAC algorithm shows a high level of fit, with a 95% match compared to the ant colony algorithm. An example analysis of the algorithm can effectively optimize the target path and achieve the least expensive transportation cost.