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On a parallel genetic-tabu search based algorithm for solving the graph colouring problem

Author

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  • Mabrouk, Bchira Ben
  • Hasni, Hamadi
  • Mahjoub, Zaher

Abstract

In this paper, we are interested in a particular combinatorial optimisation problem (COP), namely the graph colouring problem (GCP). To solve the GCP, we present a parallel approach adopting an efficient strategy. A brief survey on known methods for solving the GCP enables us to justify our approach which is based on a hybrid method, starting from a set of solutions initialized by the so-called RLF colouring method and combining both a genetic algorithm and the tabu search. A parallelising strategy is then applied. The performances of our method were evaluated through a series of experimentations achieved on an IBM SP2 multiprocessor. The processed graphs were chosen from two benchmark sets. The first, taken from the Internet, involves graphs whose chromatic numbers are known and the second involves random generated graphs. The analysis of the results proves the interest of our approach.

Suggested Citation

  • Mabrouk, Bchira Ben & Hasni, Hamadi & Mahjoub, Zaher, 2009. "On a parallel genetic-tabu search based algorithm for solving the graph colouring problem," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1192-1201, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:3:p:1192-1201
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    References listed on IDEAS

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    1. Chams, M. & Hertz, A. & de Werra, D., 1987. "Some experiments with simulated annealing for coloring graphs," European Journal of Operational Research, Elsevier, vol. 32(2), pages 260-266, November.
    2. Avanthay, Cedric & Hertz, Alain & Zufferey, Nicolas, 2003. "A variable neighborhood search for graph coloring," European Journal of Operational Research, Elsevier, vol. 151(2), pages 379-388, December.
    3. 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. Melo, Rafael A. & Queiroz, Michell F. & Santos, Marcio C., 2021. "A matheuristic approach for the b-coloring problem using integer programming and a multi-start multi-greedy randomized metaheuristic," European Journal of Operational Research, Elsevier, vol. 295(1), pages 66-81.
    2. Schryen, Guido, 2020. "Parallel computational optimization in operations research: A new integrative framework, literature review and research directions," European Journal of Operational Research, Elsevier, vol. 287(1), pages 1-18.

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