有时间窗的车辆路径问题改进蚁群算法研究  

An Improved Ant Colony Optimization for Vehicle Routing Problem with Time Windows

作　　者：董攀[1] 陈阳[1] 

机构地区：[1]长沙理工大学经济与管理学院,湖南长沙401114

出　　处：《物流科技》2014年第7期135-138,共4页Logistics Sci-Tech

摘　　要：针对目前蚁群算法在求解有时间窗的车辆路径问题上较少对蚁群算法本身进行优化的问题,提出了一种改进蚁群算法,通过改进状态转移概率和信息素更新规则,以及使用改进的精英蚂蚁策略,改善蚁群算法搜索能力。通过对Solomon标准数据集的实验,结果表明改进的蚁群算法在求解有时间窗车辆路径问题上是有效的。Current research on ant colony algorithm for vehicle routing problem with time windows, the ant colony algorithm itself is less to be optimized, so an improved ant colony algorithm was established to improve the ant colony algorithm search capabilities by improving the state transition probability and pheromone update rule, and using improved elite ant strategy. By using Solomon standard data sets, the experimental results show that the improved ant colony algorithm for solving vehicle routing problem with time windows is valid.

关 键 词：最大最小蚁群算法 有时间窗车辆路径问题 Solomon标准数据集 

分 类 号：U116.2[交通运输工程]