摘要
为了提高多配送中心车辆调度效率,该文提出了一种基于优化蚁群算法的的多配送中心车辆路径调度算法。优化算法通过对信息素挥发因子、启发式因子,信息素强度初始值的够造,消除参数选择对蚁群算法性能的影响,使其具有较强的全局搜索能力。实验表明,该文提出的基于优化蚁群算法的多配送中心车辆路径算法比其余算法有更好的实验效果。
In order to improve the the efficiency of the multiple depots vehicle routing, a new method of the improved genetic algo-rithm for the multiple depots vehicle routing isproposed. The improved algorithm eliminates the influence of the selected parame-ter by optimizingthe heuristic factor, evaporation factor, initial pheromone distribute, and have the strong globalsearching ability.The experiments demonstrate that the solving results of the improved algorithm is more excellent than the other algorithm
出处
《电脑知识与技术》
2015年第5X期190-191 197,197,共3页
Computer Knowledge and Technology
基金
山东省高等学校科技计划项目(J13LN53)
菏泽学院科学院科研基金(XY14KJ08)
关键词
蚁群算法
遗传算法
多配送中心
车辆路径优化
ant colony algorithm
genetic algorithm
multiple depots
vehicle routingoptimization
