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Deterministic Tournament Selection in Local Search for Maximum Edge Weight Clique on Large Sparse Graphs

机译:在大型稀疏图中的本地搜索最大边缘重量集团的确定性锦标赛选择

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The maximum edge weight clique (MEWC) problem is important in both theories and applications. During last decades, there has been much interest in finding optimal or near-optimal solutions to this problem. Many existing heuristics focuses on academic benchmarks of relatively small size. However, very little attention has been paid to solving the MEWC problem in large sparse graphs. In this work, we exploit the so-called deterministic tournament selection (DTS) strategy to improve the local search MEWC algorithms. Experiments conducted on a broad range of large sparse graphs show that our algorithm outperforms state-of-the-art local search algorithms in this benchmark. Moreover it finds better solutions on a list of them.
机译:最大边缘重量Clique(MEWC)问题在两个理论和应用中都很重要。在过去几十年中,有很多兴趣找到解决这个问题的最佳或接近最佳解决方案。许多现有的启发式专注于相对较小尺寸的学术基准。但是,在大稀疏图中,已经支付了很少的注意力来解决MEWC问题。在这项工作中,我们利用所谓的确定性锦标赛选择(DTS)策略来改进本地搜索MEWC算法。在广泛的大型稀疏图表中进行的实验表明,我们的算法在该基准测试中优于最先进的本地搜索算法。此外,它找到了更好的解决方案。

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