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The dynamic vehicle routing problem: Solution with hybrid metaheuristic approach

机译:动态车辆路径问题:混合元启发式方法的解决方案

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摘要

The increased awareness in just-in-time supply systems with the apparition of the new advances in communication and information technologies, have recently led researchers to focus on dynamic vehicle routing problem (DVRP). In DVRP, client requests are not known and are exposed after making some decisions. An alternative variant dynamic pickup and delivery strategy of the vehicle routing problem arises when new customers appear in the tours after the starting visit. The DVRP are among the more important and more challenging extensions of VRP. The purpose of this paper is to propose an Artificial Ant Colony based on 2_Opt local search (AAC_2_Opt) to solve the DVRP. We demonstrate the effectiveness of our approach by comparing its results with those of existing methods in the literature on the same tests problems. The AAC_2_Opt algorithm can efficiently optimize the routing problem and provide highly competitive solution.
机译:随着通信和信息技术新进展的出现,对及时供应系统的认识不断提高,最近导致研究人员将注意力集中在动态车辆路径问题(DVRP)上。在DVRP中,客户端请求是未知的,在做出某些决定后会公开。当新客户在开始拜访后出现在巡回演出中时,就会出现车辆路线选择问题的另一种动态提取和交付策略。 DVRP是VRP的更重要且更具挑战性的扩展之一。本文的目的是提出一种基于2_Opt局部搜索(AAC_2_Opt)的人工蚁群来解决DVRP。通过将其结果与文献中针对相同测试问题的现有方法进行比较,我们证明了该方法的有效性。 AAC_2_Opt算法可以有效地优化路由问题并提供极具竞争力的解决方案。

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