基于改进蚁群算法的物流配送路径优化

摘要

The computation of the vehicle path optimization for logistics distribution is complicated. Based on the multiple vehicles' logistics distribution model with constraints,it takes advantage of improved ant colony algorithm to solve the problem of selecting the path in the process of logistics distribution. By improving the global and local updating rules for pheromone, the convergence rate and global search capability is increased, compared with the traditional ant colony algorithm. Finally, the improved ant colony algorithm is successfully applied on path optimization of scheduling multiple vehicles in the logistics distribution.%随着社会的不断进步,配送车辆最短路径优化问题已广泛应用于交通运输、网络购物、物流配送等与生产生活息息相关的问题,然而配送车辆路径优化的计算比较复杂.文中建立在带约束条件的多车辆物流配送问题模型的基础上,运用改进的蚁群算法解决物流配送过程中的路径选择问题.通过对信息索的全局和局部更新规则进行改进,和传统的最值蚁群算法进行比较,算法的收敛速度和全局搜索能力得到提高.文中最后成功将改进后的蚁群算法应用于多车辆物流调度路径优化问题.结果表明该优化算法性能受优.