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A Decomposition Heuristic for the Maximal Covering Location Problem

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  • Edson Luiz França Senne
  • Marcos Antonio Pereira
  • Luiz Antonio Nogueira Lorena

Abstract

This paper proposes a cluster partitioning technique to calculate improved upper bounds to the optimal solution of maximal covering location problems. Given a covering distance, a graph is built considering as vertices the potential facility locations, and with an edge connecting each pair of facilities that attend a same client. Coupling constraints, corresponding to some edges of this graph, are identified and relaxed in the Lagrangean way, resulting in disconnected subgraphs representing smaller subproblems that are computationally easier to solve by exact methods. The proposed technique is compared to the classical approach, using real data and instances from the available literature.

Suggested Citation

  • Edson Luiz França Senne & Marcos Antonio Pereira & Luiz Antonio Nogueira Lorena, 2010. "A Decomposition Heuristic for the Maximal Covering Location Problem," Advances in Operations Research, Hindawi, vol. 2010, pages 1-12, May.
    • Handle: RePEc:hin:jnlaor:120756
    DOI: 10.1155/2010/120756
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    Cited by:

    1. Cordeau, Jean-François & Furini, Fabio & Ljubić, Ivana, 2019. "Benders decomposition for very large scale partial set covering and maximal covering location problems," European Journal of Operational Research, Elsevier, vol. 275(3), pages 882-896.

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