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An Application of Tabu Search Heuristic for the Maximum Edge-Weighted Subgraph Problem

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  • Elder Macambira

Abstract

The purpose of this article is to describe an efficient search heuristic for the Maximum Edge-weighted Subgraph (MEwS) problem. This problem requires to find a subgraph such that the sum of the weights associated with the edges of the subgraph is maximized subject to a cardinality constraint. In this study a tabu search heuristic for the MEwS problem is proposed. Different algorithms to obtain an initial solution are presented. One neighborhood search strategy is also proposed. Preliminary computational results are reported for randomly generated test problems of MEwS problem with different densities and sizes. For most of test problems, the tabu search heuristic found good solutions. In addition, for large size test problems, the tabu search outperformed the local search heuristic appearing in the literature. Copyright Kluwer Academic Publishers 2002

Suggested Citation

  • Elder Macambira, 2002. "An Application of Tabu Search Heuristic for the Maximum Edge-Weighted Subgraph Problem," Annals of Operations Research, Springer, vol. 117(1), pages 175-190, November.
    • Handle: RePEc:spr:annopr:v:117:y:2002:i:1:p:175-190:10.1023/a:1021525624027
    DOI: 10.1023/A:1021525624027
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    Cited by:

    1. 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.
    2. Martí, Rafael & Martínez-Gavara, Anna & Pérez-Peló, Sergio & Sánchez-Oro, Jesús, 2022. "A review on discrete diversity and dispersion maximization from an OR perspective," European Journal of Operational Research, Elsevier, vol. 299(3), pages 795-813.
    3. Lozano, M. & Molina, D. & GarcI´a-MartI´nez, C., 2011. "Iterated greedy for the maximum diversity problem," European Journal of Operational Research, Elsevier, vol. 214(1), pages 31-38, October.

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