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Combining Efficient Preprocessing and Incremental MaxSAT Reasoning for MaxClique in Large Graphs

机译:在大图中结合高效预处理和增量MaxSAT推理的MaxClique

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摘要

We describe a new exact algorithm for MaxClique, called LMC (short for Large MaxClique), that is especially suited for large sparse graphs. LMC is competitive because it combines an efficient preprocessing procedure and incremental MaxSAT reasoning in a branch-and-bound scheme. The empirical results show that LMC outperforms existing exact MaxClique algorithms on large sparse graphs from real-world applications.
机译:我们描述了一种新的精确算法,用于MaxClique,称为LMC(用于大的MaxClique的短片),这尤其适用于大稀疏图。 LMC具有竞争力,因为它在分支和绑定方案中结合了高效的预处理程序和增量MaxSAT推理。实证结果表明,LMC优于现有的真实稀疏图中的现有精确的MAXCLIQUE算法。

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