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Genetic Algorithm for Graph Coloring: Exploration of Galinier and Hao's Algorithm

Author

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  • Celia A. Glass

    (Cass Business School)

  • Adam Prügel-Bennett

    (University of Southampton)

Abstract

This paper examines the best current algorithm for solving the Chromatic Number Problem, due to Galinier and Hao (Journal of Combinatorial Optimization, vol. 3, no. 4, pp. 379–397, 1999). The algorithm combines a Genetic Algorithm with Tabu Search. We show that the algorithm remains powerful even if the Tabu Search component is eliminated, and explore the reasons for its success where other Genetic Algorithms have failed. In addition we propose a generalized algorithm for the Frequency Assignment Problem.

Suggested Citation

  • Celia A. Glass & Adam Prügel-Bennett, 2003. "Genetic Algorithm for Graph Coloring: Exploration of Galinier and Hao's Algorithm," Journal of Combinatorial Optimization, Springer, vol. 7(3), pages 229-236, September.
    • Handle: RePEc:spr:jcomop:v:7:y:2003:i:3:d:10.1023_a:1027312403532
    DOI: 10.1023/A:1027312403532
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    References listed on IDEAS

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    1. David S. Johnson & Cecilia R. Aragon & Lyle A. McGeoch & Catherine Schevon, 1991. "Optimization by Simulated Annealing: An Experimental Evaluation; Part II, Graph Coloring and Number Partitioning," Operations Research, INFORMS, vol. 39(3), pages 378-406, June.
    2. Philippe Galinier & Jin-Kao Hao, 1999. "Hybrid Evolutionary Algorithms for Graph Coloring," Journal of Combinatorial Optimization, Springer, vol. 3(4), pages 379-397, December.
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    Cited by:

    1. Xiao-Feng Xie & Jiming Liu, 2009. "Graph coloring by multiagent fusion search," Journal of Combinatorial Optimization, Springer, vol. 18(2), pages 99-123, August.

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