A fast local search based memetic algorithm for the parallel row ordering problem

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2025-02-01 Epub Date: 2024-08-28 DOI:10.1016/j.amc.2024.129040
Gintaras Palubeckis
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Abstract

The parallel row ordering problem (PROP) is concerned with arranging two groups of facilities along two parallel lines with the goal of minimizing the sum of the flow cost-weighted distances between the pairs of facilities. As the main result of this paper, we show that the insertion neighborhood for the PROP can be explored in optimal time Θ(n2) by providing an O(n2)-time procedure for performing this task, where n is the number of facilities. As a case study, we incorporate this procedure in a memetic algorithm (MA) for solving the PROP. We report on numerical experiments that we conducted with MA on PROP instances with up to 500 facilities. The experimental results demonstrate that the MA is superior to the adaptive iterated local search algorithm and the parallel hyper heuristic method, which are state-of-the-art for the PROP. Remarkably, our algorithm improved best known solutions for six largest instances in the literature. We conjecture that the time complexity of exploring the interchange neighborhood for the PROP is Θ(n2), exactly as in the case of insertion operation.

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基于局部搜索的并行排序问题快速记忆算法
并行排序问题(PROP)涉及沿两条并行线排列两组设施,目标是使两组设施之间的流量成本加权距离之和最小。作为本文的主要成果,我们展示了 PROP 的插入邻域可以在最优时间 Θ(n2) 内探索,提供了一个 O(n2)-time 的程序来执行这项任务,其中 n 是设施的数量。作为一项案例研究,我们将这一程序纳入了用于求解 PROP 的记忆算法 (MA)。我们报告了在多达 500 个设施的 PROP 实例上使用 MA 进行的数值实验。实验结果表明,记忆算法优于自适应迭代局部搜索算法和并行超启发式方法,而这两种算法在 PROP 方面都是最先进的。值得注意的是,我们的算法改进了文献中六种最大实例的已知最佳解决方案。我们推测,探索 PROP 交换邻域的时间复杂度为 Θ(n2),与插入操作的情况完全相同。
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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