文献类型：会议论文

英文题名：An ant colony algorithm with stochastic local search for the VRP

作者：Qi, Chengming[1]

第一作者：亓呈明

通讯作者：Qi, C.

机构：[1] College of Automation, Beijing Union University, Beijing, 100101, China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]College of Automation, Beijing Union University, Beijing, 100101, China|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：3rd International Conference on Innovative Computing Information and Control, ICICIC'08

会议日期：June 18, 2008 - June 20, 2008

会议地点：Dalian, Liaoning, China

语种：英文

外文关键词：Combinatorial optimization - Learning algorithms - Local search (optimization) - Stochastic systems - Vehicle routing

摘要：In recent years there has been growing interest in algorithms inspired by the observation of natural phenomena to define computational procedures which can solve complex problems. In this paper, through an analysis of the constructive procedure of the solution in the Ant Colony System (ACS), a Vehicle Routing Problem (VRP) is examined and a hybrid ant colony system coupled with a stochastic local search algorithm(SLSACS), is proposed. In SLSACS, only partial customers are randomly chosen to compute the transition probability. Experiments on various aspects of the algorithm and computational results for fourteen bench-mark problems are reported. We compare our approach with ACS, some other classic, powerful meta-heuristics and show that our results are competitive. ? 2008 IEEE.