Integrated genetic algorithm with hill climbing for bandwidth minimization problem

  • Authors:

  • Andrew Lim;Brian Rodrigues;Fei Xiao

  • Affiliations:

  • Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology, Hong Kong;School of Business, Singapore Management University, Singapore;Department of Computer Science, National University of Singapore, Singapore

  • Venue:
  • GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
  • Year:
  • 2003

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Abstract

In this paper, we propose an integrated Genetic Algorithm with Hill Climbing to solve the matrix bandwidth minimization problem, which is to reduce bandwidth by permuting rows and columns resulting in the nonzero elements residing in a band as close as possible to the diagonal. Experiments show that this approach achieves the best solution quality when compared with the GPS [1] algorithm, Tabu Search [3], and the GRASP with Path Relinking methods [4], while being faster than the latter two newly-developed heuristics.