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AN EFFECTIVE REFINEMENT ALGORITHM BASED ON MULTILEVEL PARADIGM FOR GRAPH BIPARTITIONING

机译:基于多层次范式的图形分组有效细化算法

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摘要

The min-cut bipartitioning problem is a fundamental partitioning problem and is NP-Complete. It is also NP-Hard to find good approximate solutions for this problem. In this paper, we present a new effective refinement algorithm based on multilevel paradigm for graph bipartitioning. The success of our algorithm relies on exploiting both new Tabu search strategy and boundary refinement policy. Our experimental evaluations on 18 different graphs show that our algorithm produces excellent solutions compared with those produced by MeTiS that is a state-of-the-art partitioner in the literature.
机译:最小割分问题是一个基本的分问题,并且是NP完全的。为这个问题找到好的近似解决方案也是NP-Hard。在本文中,我们提出了一种新的基于多级范式的有效细化算法进行图分割。我们算法的成功依赖于开发新的禁忌搜索策略和边界细化策略。我们对18张不同图形进行的实验评估表明,与文献中最先进的分区器MeTiS相比,我们的算法可提供出色的解决方案。

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