A fix-and-optimize matheuristic for the k-labelled spanning forest problem

Tiago F.D. Pinheiro, S. V. Ravelo, L. Buriol
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Abstract

In this paper, we study the k-labeled spanning forest problem (kLSF). The input for this problem is an undirected graph with labeled edges and a positive integer k. The goal is to find a spanning forest of the graph with at most $k$ different labels associated with the edges, minimizing the number of components. kLSF finds practical applications in different scenarios related to networks design and telecommunications. Solving it may help to reduce the negative impact of electromagnetic fields exposure on the population health or to increase profits of internet management companies, among others. The interest in kLSF is not only practical but also theoretical since the problem generalizes the best-known NP-hard minimum labeling spanning tree problem (MLST). To approach kLSF, we propose a fix-and-optimize matheuristic that was tested over several instances, achieving high-quality solutions in reasonable computational time. When compared to the best-known algorithms in the literature, our matheuristic outperformed the other proposals in most cases, finding better solutions in less computational time for the most challenging instances.
k标记生成森林问题的固定优化数学方法
本文研究了k标记生成森林问题(kLSF)。这个问题的输入是一个无向图,有标记的边和一个正整数k。目标是找到一个图的生成森林,与边相关联的标签最多为$k$,最小化组件的数量。kLSF在与网络设计和电信相关的不同场景中找到了实际应用。解决这一问题可能有助于减少电磁场暴露对人口健康的负面影响,或增加互联网管理公司的利润等。对kLSF的兴趣不仅是实际的,而且是理论上的,因为该问题推广了最著名的NP-hard最小标记生成树问题(MLST)。为了接近kLSF,我们提出了一种修复和优化的数学方法,该方法在几个实例上进行了测试,在合理的计算时间内获得了高质量的解决方案。当与文献中最著名的算法相比时,我们的数学方法在大多数情况下优于其他建议,在最具挑战性的实例中以更少的计算时间找到更好的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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