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A branch-and-price algorithm for the Minimum Latency Problem

机译:最小延迟问题的分支价格算法

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This paper deals with the Minimum Latency Problem (MLP), a variant of the well-known Traveling Salesman Problem in which the objective is to minimize the sum of waiting times of customers. This problem arises in many applications where customer satisfaction is more important than the total time spent by the server. This paper presents a novel branch-and-price algorithm for MLP that strongly relies on new features for the ng-path relaxation, namely: (1) a new labeling algorithm with an enhanced dominance rule named multiple partial label dominance; (2) a generalized definition of ng-sets in terms of arcs, instead of nodes; and (3) a strategy for decreasing ng-set sizes when those sets are being dynamically chosen. Also, other elements of efficient exact algorithms for vehicle routing problems are incorporated into our method, such as reduced cost fixing, dual stabilization, route enumeration and strong branching. Computational experiments over TSPLIB instances are reported, showing that several instances not solved by the current state-of-the-art method can now be solved. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文讨论了最小延迟问题(MLP),它是著名的旅行推销员问题的一种变体,其目的是最大程度地减少客户的等待时间之和。在许多应用中会出现此问题,在这些应用中,客户满意度比服务器花费的总时间更为重要。本文提出了一种新的MLP分支价格算法,该算法强烈依赖于ng-path松弛的新特征,即:(1)一种具有增强的优势规则的新标记算法,称为多部分标签优势。 (2)关于弧集而不是节点的ng集的广义定义; (3)当动态选择ng-set大小时,减小ng-set大小的策略。同样,针对车辆路径问题的高效精确算法的其他元素也已合并到我们的方法中,例如降低成本固定,双重稳定,路径枚举和强大分支。报告了在TSPLIB实例上进行的计算实验,结果表明,现在可以解决当前最新技术无法解决的几个实例。 (C)2018 Elsevier Ltd.保留所有权利。

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