首页 | 新闻公告 | 作者指南 | 编委会 | 关于杂志 | 订阅 | 相关链接 | 下载区 | 联系我们

车辆路径问题的混合蚁群算法设计与实现
Design and realization of a hybrid ant colony algorithm for vehicle muting problem
摘要点击 7984  全文点击 6285    
查看全文  查看/发表评论  下载PDF阅读器
中文关键词  车辆路径问题 旅行商问题 蚁群算法 爬山法 近似解可行化
英文关键词  vehicle routing problem; traveling salesman problem; ant colony algorithm; 2-opt; feasibility process of approximate solutions
基金项目  
学科分类代码  
作者单位
刘志硕 申金升 关伟 北京交通大学交通运输学院系统工程与控制研究所 
中文摘要
      蚁群算法是一种新型的模拟进化算法,具有许多优良的性质,可以很好地解决TSP问题.在分析车辆路径问题(VRP)与佟P区别的基础上,论文将蚁群算法应用于VRP的求解,针对VRP的具体特点,构造了具有自适应功能的混合蚁群算法.该算法对基本规则作了进一步改进,并有机结合了爬山法、节约法等方法,以减少计算时间,避免算法停滞.指出可行解问题是蚁群算法的关键问题,提出了大蚂蚁数、近似解可行化等四个解决策略.计算机仿真结果表明,自适应混合蚁群算法性能优良,能够有效地求解VRP
英文摘要
      Ant Colony Algorithm(ACA) is a novel simulated evolutionary algorithm which shows many promising properties and can solve Traveling Salesman Problem(TSP) efficiently. On the basis of analyzing the difference between VRP and TSP, an Adaptive Hybrid Ant Colony Algorithm(AHACA) is proposed to solve VRP, which is improved from basic ACA by improving the basic rules and integrating 2-opt local search method and C-W algorithm in order to decrease computing time and avoid stagnation behavior of basic ACA. Moreover, the problem of acquiring feasible solution is also discussed, and four resolutions such as Mass Ant, Feasibility Process of Approximate Solutions etc. are also introduced. Simulation results show that the AHACA is feasible and valid for VRP
关闭

版权所有 © 2007 《管理科学学报》
通讯地址:天津市南开区卫津路92号天津大学第25教学楼A座908室 邮编:300072
联系电话/传真:022-27403197 电子信箱: jmstju@263.net