平均最优信息粒子群算法在车辆调度中的应用  

Particle Swarm Optimization Based on the Average Optimal Information for Vehicle Routing Problem

作　　者：李壮阔[1] 马艳楠[1] 刘亮[1] 

机构地区：[1]桂林电子科技大学商学院,广西桂林541004

出　　处：《物流科技》2013年第7期50-54,共5页Logistics Sci-Tech

基　　金：广西自然科学基金资助项目;项目编号:2012jjDAG0009

摘　　要：针对标准粒子群算法在求解车辆调度问题中存在的易陷入局部最优、早熟等缺陷,从粒子群算法本身出发,引入粒子个体与群体的平均信息,提出一种基于平均最优信息的粒子群算法(AVGPSO),该算法利用粒子个体最优信息和全局最优信息的平均值来提高全局搜索能力。将该算法应用到车辆调度问题中,并与标准粒子群算法进行比较。实验结果表明,该算法在解决车辆调度问题中表现出了更优的性能,是解决车辆调度问题的有效方法。According to the weakness of standard particle swarm optimization in dealing with vehicle ro＇ problem （VRP）, based on the definition of particle swarm optimization, this paper introduce the average information of lnd and and the global information to the standard PSO. A new hybrid form of PSO （AVGPSO）, which is based on the mean information of individual optimal information and the global optimal information, is brought forward. This proposed algorithm is applied to VRP and Com- pared with standard particle swarm optimization. The result shows that the ed m has better probability for soling VRP.

关 键 词：车辆调度问题 粒子群算法 平均最优信息 组合优化 

分 类 号：U116.2[交通运输工程]