An effective multilevel tabu search approach for balanced graph partitioning

  • Authors:

  • Una Benlic;Jin-Kao Hao

  • Affiliations:

  • LERIA, Université d'Angers, 2 Boulevard Lavoisier, 49045 Angers Cedex 01, France;LERIA, Université d'Angers, 2 Boulevard Lavoisier, 49045 Angers Cedex 01, France

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2011

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Abstract

Graph partitioning is one of the fundamental NP-complete problems which is widely applied in many domains, such as VLSI design, image segmentation, data mining, etc. Given a graph G=(V,E), the balanced k-partitioning problem consists in partitioning the vertex set V into k disjoint subsets of about the same size, such that the number of cutting edges is minimized. In this paper, we present a multilevel algorithm for balanced partition, which integrates a powerful refinement procedure based on tabu search with periodic perturbations. Experimental evaluations on a wide collection of benchmark graphs show that the proposed approach not only competes very favorably with the two well-known partitioning packages METIS and CHACO, but also improves more than two thirds of the best balanced partitions ever reported in the literature.