4.7 Article

A hybrid algorithm for vehicle routing problem with time windows

期刊

EXPERT SYSTEMS WITH APPLICATIONS
卷 38, 期 1, 页码 435-441

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2010.06.082

关键词

VRPTW; Ant colony optimization; Neighborhood search; Tabu search

资金

  1. National Science Foundation for Post-doctoral Scientists of China [20080440168]
  2. Doctoral Program Foundation for Young Scholar of Institutions of Higher Education of China [20070151013]
  3. Dalian maritime university [2009QN094]

向作者/读者索取更多资源

Vehicle routing problem with time windows (VRPTVV) is a well-known combinatorial problem. Many researches have presented meta-heuristics are effective approaches for VRPTW. This paper proposes a hybrid approach, which consists of ant colony optimization (ACO) and Tabu search, to solve the problem. To improve the performance of ACO, a neighborhood search is introduced. Furthermore, when ACO is close to the convergence Tabu search is used to maintain the diversity of ACO and explore new solutions. Computational experiments are reported for a set of the Solomon's 56 VRPTW and the approach is compared with some meta-heuristic published in literature. Results show that considering the tradeoff of quality and computation time, the hybrid algorithm is a competitive approach for VRPTVV. (C) 2010 Elsevier Ltd. All rights reserved.

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