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A hybrid iterated local search heuristic for the maximum weight independent set problem

机译:一个混合迭代本地搜索启发式最大重量独立集

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摘要

This paper presents a hybrid iterated local search (ILS) algorithm for the maximum weight independent set (MWIS) problem, a generalization of the classical maximum independent set problem. Two efficient neighborhood structures are proposed and they are explored using the variable neighborhood descent procedure. Moreover, we devise a perturbation mechanism that dynamically adjusts the balance between intensification and diversification during the search. The proposed algorithm was tested on two well-known benchmarks (DIMACS-W and BHOSLIB-W) and the results obtained were compared with those found by state-of-the-art heuristics and exact methods. Our heuristic outperforms the best-known heuristic for the MWIS as well as the best heuristics for the maximum weight clique problem. The results also show that the hybrid ILS was capable of finding all known optimal solutions in milliseconds.
机译:本文介绍了一个混合迭代本地搜索(ILS)算法,用于最大重量独立集(MWIS)问题,是经典最大独立设置问题的概念。 提出了两个有效的邻域结构,并使用可变邻域血液抑制过程探索它们。 此外,我们设计了一种扰动机制,可以在搜索期间动态调整强化和多样化之间的平衡。 在两个众所周知的基准(DIMACS-W和BHOSLIB-W)上测试了所提出的算法,并将获得的结果与最先进的启发式和精确方法发现的结果进行了比较。 我们的启发式胜过了MWIS最着名的启发式,以及最大重量集团问题的最佳启发式。 结果还表明,杂交ILS能够以毫秒为单位找到所有已知的最佳解决方案。

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