计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (15): 47-50.DOI: 10.3778/j.issn.1002-8331.2010.15.015

• 研究、探讨 • 上一篇    下一篇

考虑工作量平衡的多旅行商问题及其求解

刘伟民1,2,李苏剑1,郑爱云2,赵方庚3   

  1. 1.北京科技大学 机械工程学院 物流工程系,北京 100083
    2.河北理工大学 机械工程学院,河北 唐山063009
    3.汽车管理学院 车管系,安徽 蚌埠 233011
  • 收稿日期:2008-12-02 修回日期:2009-03-02 出版日期:2010-05-21 发布日期:2010-05-21
  • 通讯作者: 刘伟民

Multiple traveling salesmen problem with workload balance and its resolution

LIU Wei-min1,2,LI Su-jian1,ZHENG Ai-yun2,ZHAO Fang-geng3   

  1. 1.Department of Logistics Engineering,School of Mechanical Engineering,University of Science and Technology Beijing,Beijing 100083,China
    2.School of Mechanical Engineering,Hebei Polytechnic University,Tangshan,Hebei 063009,China
    3.Department of Vehicle Management,Vehicle Management Institute,Bengbu,Anhui 233011,China
  • Received:2008-12-02 Revised:2009-03-02 Online:2010-05-21 Published:2010-05-21
  • Contact: LIU Wei-min

摘要: 根据多旅行商问题(MTSP)特点,针对最小化各旅行商最长路线这一优化目标,提出改进蚁群算法(IACO)。最小化各旅行商最长路线考虑各旅行商的工作量平衡,更具实际应用意义。算法中信息素更新与限制遵循最大最小蚁群算法(MMAS)框架,为提高算法性能设计混合局域搜索算法。利用文献中标准算例进行检验,结果表明,所设计蚁群算法与三种遗传算法相比表现出较强竞争性。

关键词: 蚁群算法, 局域搜索算法, 多旅行商问题

Abstract: An improved ant colony optimization(IACO) algorithm for the MTSP is proposed.The optimized objective is that minimizing the maximum tour length of each salesman which related with balancing the workload among salesmen.The minmax objective has more application meaning in practice.In the algorithm,the pheromone trail updating and limits follow the MAX-MIN Ant System(MMAS) scheme,and a hybrid local search procedure is designed to improve the performance of the algorithm.The proposed algorithm is tested using some benchmark instances in literatures and compared with three genetic algorithms(GA).The experimental results show that the proposed algorithm is competitive.

Key words: ant colony optimization, local search, Multiple Traveling Salesmen Problem(MTSP)

中图分类号: