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An ant colony optimization model: The period vehicle routing problem with time windows

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  • Yu, Bin
  • Yang, Zhong Zhen
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    Abstract

    This paper proposes an improved ant colony optimization (IACO) to solve period vehicle routing problem with time windows (PVRPTW), in which the planning period is extended to several days and each customer must be served within a specified time window. Multi-dimension pheromone matrix is used to accumulate heuristic information on different days. Two-crossover operations are introduced to improve the performance of the algorithm. The effectiveness of IACO is evaluated using a set of well-known benchmarks. Some of the results are better than the best-known solutions. Results also show the IACO seems to be a powerful tool for PVRPTW.

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    File URL: http://www.sciencedirect.com/science/article/pii/S136655451000089X
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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.

    Volume (Year): 47 (2011)
    Issue (Month): 2 (March)
    Pages: 166-181

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    Handle: RePEc:eee:transe:v:47:y:2011:i:2:p:166-181

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    Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description

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    Related research

    Keywords: Period vehicle routing problem with time windows Ant colony optimization Multi-dimension pheromone Crossover operation;

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    Cited by:
    1. Tu, Wei & Fang, Zhixiang & Li, Qingquan & Shaw, Shih-Lung & Chen, BiYu, 2014. "A bi-level Voronoi diagram-based metaheuristic for a large-scale multi-depot vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 84-97.
    2. Liu, Ran & Xie, Xiaolan & Garaix, Thierry, 2014. "Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics," Omega, Elsevier, vol. 47(C), pages 17-32.

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