A gradient method on the initial partition of Fiduccia-Mattheyses algorithm

  title={A gradient method on the initial partition of Fiduccia-Mattheyses algorithm},
  author={Lung-Tien Liu and Ming-Ter Kuo and Shih-Chen Huang and Chung-Kuan Cheng},
In this paper, a Fiduccia-Mattheyses (FM) algorithm incorporating a novel initial partition generating method is proposed. The proposed algorithm applies to both bipartitioning and multi-way partitioning problems with or without replication. The initial partition generating method is based on a gradient decent algorithm. On partitioning without replication, our algorithm achieves an average of 17% improvement over the analytical method, PARABOLI, on bipartitioning, 10% better than Primal-Dual… CONTINUE READING
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