基于改进蚁群算法的车辆路径优化问题研究

摘要

物流活动中需要找出各个配货节点之间的最短路径,用以指导物流车辆调度,进而节约物流成本.提出解决车辆路径优化问题的方法,针对蚁群算法的缺点,分别对信息素更新策略、启发因子进行改进,并引入搜索热区机制,有效解决了蚁群算法的缺陷.最后,以哈尔滨市局部地图为原型,应用MATLAB软件对改进蚁群算法求解车辆路径优化问题的性能进行仿真,并与基本蚁群算法对比分析,验证了改进蚁群算法的有效性和可行性.%Logistics activities need to find different distribution node of the shortest path, to instruct the logistics vehicle scheduling, and then save the logistics cost. This paper proposed the solution of vehicle routing optimization problem. In order to conquer the defects and improve the basic ant colony optimization, it improved pheromones updating strategy, stimulating factor and the introduction of search hotspots, solved the defects of ant colony optimization effectively. With the help of Harbin city map as the prototype and the MATLAB software, it carried out simulation to check the improved ant colony optimization. The result verifies the feasibility and effectiveness of the improved ant colony optimization.