两级定位-路径问题模型及变邻域粒子群算法

为满足B2C电子商务中高效率、低成本配送需求,建立了两级定位-路径问题的三下标车流模型,提出了一种求解该问题的变邻域粒子群算法。该算法引入路径重连思想,将粒子群算法中粒子动态更新设计为当前解的邻域搜索、当前解与个体历史最优解之间的路径重连、当前解与种群历史最优解之间的路径重连;在此基础上,提出变邻域搜索策略,动态改变邻域结构以拓展搜索空间。实验结果表明,该算法能有效求解两级定位-路径问题。

A Mathematical Model and Particle Swarm Optimization with Variable Neighborhood Search for Two Location-Routing Problem

In order to meet the high-efficiency and low-cost distribution needs of B2C e-commerce, a mathematical model based on three-index vehicle flow for two-echelon location-routing problem is established. Particle swarm optimization with variable neighborhood search is put forward to solve this problem. Path relinking is used in this algorithm. Particle dynamic update is designed as some operations, such as neighborhood search of current solution, path relinking between current solution and the individual historical optimal solution, path relinking between the current solution and the population historical optimal solution. Based on this, variable neighborhood search strategies are put forward to change the neighborhood structure dynamically to expand the search space. The experimental results show that this algorithm can solve two-echelon location-routing problem effectively.