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An efficient approach for large scale graph partitioning

机译:大规模图形分割的有效方法

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In this paper, we consider the problem of partitioning the set of vertices of a graph intok subsets of approximately the same cardinality in such a way that the number of edges whose endpoints are in different subsets is minimized. A greedy heuristic, called Procedure1, based on the independent growth of each subset by fronts is proposed for constructing a good-quality graph partition. In addition, we present a more sophisticated version of the greedy heuristic, called Procedure2, which periodically calls a routine to refine the partition being built. We show that the partitions generated by Procedure1 are competitive with those obtained by several constructive heuristics in the literature, e.g. spectral, geometric, as well as other greedy heuristics. Moreover, the partitions produced by Procedure2 are compared with those produced by a leading graph partitioning method in the literature.
机译:在本文中,我们考虑将图的顶点集划分为大致相同基数的k个子集的问题,以使端点位于不同子集中的边的数量最小化。提出了一种贪婪的启发式方法,称为procedure1,该方法基于每个子集的前沿独立增长,以构造高质量的图分区。此外,我们还提供了一个更为复杂的贪婪启发式方法,称为Procedure2,该程序定期调用例程以完善正在构建的分区。我们表明,由Procedure1生成的分区与文献中几种构造启发式方法获得的分区具有竞争力,例如频谱,几何以及其他贪婪启发式算法。此外,将Procedure2产生的分区与文献中通过超前图划分方法产生的分区进行了比较。

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