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A Path Relinking Approach with an Adaptive Mechanism to Control Parameters for the Vehicle Routing Problem with Time Windows

机译:具有时间窗的车辆路径问题的自适应机制路径重新链接方法

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We propose a path relinking approach for the vehicle routing problem with time windows. The path relinking is an evolutionary mechanism that generates new solutions by combining two or more reference solutions. In our algorithm, those solutions generated by path relinking operations are improved by a local search whose neighborhood consists of slight modifications of the representative neighborhoods called 2-opt*, cross exchange and Or-opt. To make the search more efficient, we propose a neighbor list that prunes the neighborhood search heuristically. Infeasible solutions are allowed to be visited during the search, while the amount of violation is penalized. As the performance of the algorithm crucially depends on penalty weights that specify how such penalty is emphasized, we propose an adaptive mechanism to control the penalty weights. The computational results on well-studied benchmark instances with up to 1000 customers revealed that our algorithm is highly efficient especially for large instances. Moreover, it updated 41 best known solutions among 356 instances.
机译:我们提出了一种带有时间窗的车辆路径问题的路径重新链接方法。路径重新链接是一种进化机制,可以通过组合两个或更多参考解决方案来生成新解决方案。在我们的算法中,通过路径重新链接操作生成的那些解决方案通过局部搜索得到了改善,该搜索的邻域由对代表性邻域的稍作修改(称为2-opt *,交叉交换和Or-opt)组成。为了提高搜索效率,我们提出了一个邻居列表,该列表会启发式地修剪邻居搜索。在搜索过程中允许访问不可行的解决方案,同时对违规行为进行处罚。由于算法的性能关键取决于指定惩罚方式的惩罚权重,因此我们提出了一种自适应机制来控制惩罚权重。对经过研究的基准实例(最多可容纳1000个客户)的计算结果表明,我们的算法非常有效,特别是对于大型实例。此外,它还更新了356个实例中的41个最著名的解决方案。

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