An Effective Refinement Algorithm Based on Multilevel Paradigm for Graph Bipartitioning

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.

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