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Think Locally, Act Globally:Highly Balanced Graph Partitioning

机译:本地思考,全球行动:高度平衡的图形分区

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We present a novel local improvement scheme for graph partitions that allows to enforce strict balance constraints. Using negative cycle detection algorithms this scheme combines local searches that individually violate the balance constraint into a more global feasible improvement. We combine this technique with an algorithm to balance unbalanced solutions and integrate it into a parallel multi-level evolutionary algorithm, KaFFPaE, to tackle the problem. Overall, we obtain a system that is fast on the one hand and on the other hand is able to improve or reproduce many of the best known perfectly balanced partitioning results reported in the Walshaw benchmark.
机译:我们为图形分区提出了一种新颖的局部改进方案,该方案可以强制执行严格的平衡约束。该方案使用负周期检测算法,将局部违反平衡约束的局部搜索组合成更全面的可行改进方法。我们将此技术与一种算法相结合以平衡不平衡的解决方案,并将其集成到并行的多级进化算法KaFFPaE中,以解决该问题。总体而言,我们一方面获得了一个快速的系统,另一方面又可以改善或重现Walshaw基准报告中许多最著名的完美平衡分区结果。

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