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An efficient memetic algorithm for the graph partitioning problem

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  • Philippe Galinier
  • Zied Boujbel
  • Michael Coutinho Fernandes

Abstract

Given a graph and an integer k, the goal of the graph partitioning problem is to find a partition of the vertex set in k classes, while minimizing the number of cut edges, and respecting a balance constraint between the classes. In this paper, we present a new memetic algorithm for the solution of the problem which uses both a tabu operator and a specialized crossover operator. The algorithm is tested by using the benchmarks of the graph partitioning archive. Our experiments show our memetic algorithm to outperform state-of-the-art algorithms proposed so far for the problem and to reach new records for a majority of the tested benchmarks instances. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Philippe Galinier & Zied Boujbel & Michael Coutinho Fernandes, 2011. "An efficient memetic algorithm for the graph partitioning problem," Annals of Operations Research, Springer, vol. 191(1), pages 1-22, November.
    • Handle: RePEc:spr:annopr:v:191:y:2011:i:1:p:1-22:10.1007/s10479-011-0983-3
    DOI: 10.1007/s10479-011-0983-3
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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. Chris Walshaw, 2004. "Multilevel Refinement for Combinatorial Optimisation Problems," Annals of Operations Research, Springer, vol. 131(1), pages 325-372, October.
    3. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    4. 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. Lin, Geng & Guan, Jian & Feng, Huibin, 2018. "An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 199-209.
    2. Jiawei Song & Yang Wang & Haibo Wang & Qinghua Wu & Abraham P. Punnen, 2019. "An effective multi-wave algorithm for solving the max-mean dispersion problem," Journal of Heuristics, Springer, vol. 25(4), pages 731-752, October.
    3. Wu, Qinghua & Hao, Jin-Kao, 2013. "A hybrid metaheuristic method for the Maximum Diversity Problem," European Journal of Operational Research, Elsevier, vol. 231(2), pages 452-464.
    4. Raka Jovanovic & Abdelkader Bousselham & Stefan Voß, 2015. "A heuristic method for solving the problem of partitioning graphs with supply and demand," Annals of Operations Research, Springer, vol. 235(1), pages 371-393, December.
    5. Yi Zhou & Jin-Kao Hao & Adrien Goëffon, 2016. "A three-phased local search approach for the clique partitioning problem," Journal of Combinatorial Optimization, Springer, vol. 32(2), pages 469-491, August.
    6. Zhou, Qing & Benlic, Una & Wu, Qinghua & Hao, Jin-Kao, 2019. "Heuristic search to the capacitated clustering problem," European Journal of Operational Research, Elsevier, vol. 273(2), pages 464-487.

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