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基于带时间窗的车辆路径问题的蚁群算法 被引量:5

Ant Colony Algorithm Based on Vehicle Routing Problem with Time Windows
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摘要 针对带时间窗车辆路径问题(Vehicle Routing Problem with Time Windows,VRPTW)的特点,对蚁群算法进行了改进,优化了其搜索解的能力和收敛速度,用实例证明了改进的蚁群算法对解决VRPTW的有效性. Based on the characteristics of Vehicle Routing Problem with Time Windows (VRPTW), an improved Ant Colony Algorithm is proposed in this paper, the ability of finding efficient solutions and the convergence speed are optimized with this algorithm, and the computational experiment demonstrates that the improved algorithm is efficient to the VRPTW.
出处 《重庆工学院学报》 2007年第11期50-52,共3页 Journal of Chongqing Institute of Technology
关键词 蚁群算法 带时间窗车辆路径问题 信息素 优化 Ant Colony Algorithm VRPTW pheromone optimization
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  • 1Taillard D,Badeau P,Gendreau M F,et al.Atabusearch heuristic for the vehicle routing problem with soft time windows[J].Transportation Science,1997,31(2):170-186.
  • 2GambardellaLM,Taillard E D,AgazziG.MACS-VRPTW:a multiple ant colony system for vehicle routing problems with time windows[A].In Corne D,Dorigo M,Glover F.New Ideas in Optimization[C].London:McGraw Hill,1999.
  • 3Dorigo M,Stutzle T.Ant colony optimization[M].Cambridge,Massachusetts,Lodon:MIT Press,2004.
  • 4Changchien W S,Wu C S.An ant colony system for vehicle routing problems with time window[A].Proceedings of the Seventh Conference on Artificial Intelligence and Applications[C].Taiwan:TAAI2002,C6-1,2002.
  • 5Chiang W C,Russell R A.A reactive tabu search metaheuristic for the vehicle routing problem with time windows[J].INFORMS Journal on Computing,1997,9:417-430.
  • 6Rochat Y,Taillard E.Probabilistic diversification and intensification in local search for vehicle routing[J].Journal of Heuristic,1995,(1):147-167.
  • 7Chu S C,Hohn F,Jeng S Y.Ant colony system with communication strategies[J].Information Sciences,2004,167 (1-4):63-76.
  • 8庄昌文,范明钰,李春辉,虞厥邦.基于协同工作方式的一种蚁群布线系统[J].Journal of Semiconductors,1999,20(5):400-406. 被引量:17
  • 9吴庆洪,张纪会,徐心和.具有变异特征的蚁群算法[J].计算机研究与发展,1999,36(10):1240-1245. 被引量:306
  • 10张纪会,高齐圣,徐心和.自适应蚁群算法[J].控制理论与应用,2000,17(1):1-3. 被引量:150

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