A New Multi-level Algorithm Based on Particle Swarm Optimization for Bisecting Graph

Authors:
Lingyu Sun;Ming Leng;Songnian Yu
Affiliations:
Department of Computer Science, Jinggangshan College, Ji'an, 343009, PR China;School of Computer Engineering and Science, Shanghai University, Shanghai, 200072, PR China;School of Computer Engineering and Science, Shanghai University, Shanghai, 200072, PR China
Venue:
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Year:
2007

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Abstract

An important application of graph partitioning is data clustering using a graph model -- the pairwise similarities between all data objects form a weighted graph adjacency matrix that contains all necessary information for clustering. The min-cut bipartitioning problem is a fundamental graph partitioning problem and is NP-Complete. In this paper, we present a new multi-level algorithm based on particle swarm optimization (PSO) for bisecting graph. The success of our algorithm relies on exploiting both the PSO method and the concept of the graph core. Our experimental evaluations on 18 different graphs show that our algorithm produces encouraging solutions compared with those produced by MeTiS that is a state-of-the-art partitioner in the literature.