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  • 标题:Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm
  • 本地全文:下载
  • 作者:Zhengyu Duan ; Shichao Sun ; Shuo Sun
  • 期刊名称:Advances in Mechanical Engineering
  • 印刷版ISSN:1687-8140
  • 电子版ISSN:1687-8140
  • 出版年度:2015
  • 卷号:7
  • 期号:11
  • DOI:10.1177/1687814015618631
  • 语种:English
  • 出版社:Sage Publications Ltd.
  • 摘要:This article addresses the stochastic time-dependent vehicle routing problem. Two mathematical models named robust optimal schedule time model and minimum expected schedule time model are proposed for stochastic time-dependent vehicle routing problem, which can guarantee delivery within the time windows of customers. The robust optimal schedule time model only requires the variation range of link travel time, which can be conveniently derived from historical traffic data. In addition, the robust optimal schedule time model based on robust optimization method can be converted into a time-dependent vehicle routing problem. Moreover, an ant colony optimization algorithm is designed to solve stochastic time-dependent vehicle routing problem. As the improvements in initial solution and transition probability, ant colony optimization algorithm has a good performance in convergence. Through computational instances and Monte Carlo simulation tests, robust optimal schedule time model is proved to be better than minimum expected schedule time model in computational efficiency and coping with the travel time fluctuations. Therefore, robust optimal schedule time model is applicable in real road network.
  • 关键词:Vehicle routing problem; stochastic time-dependent network; robust optimization; ant colony algorithm
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