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Some heuristic methods for solving p-median problems with a coverage constraint

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  • Sáez-Aguado, Jesús
  • Trandafir, Paula Camelia

Abstract

The aim of this paper is to solve p-median problems with an additional coverage constraint. These problems arise in location applications, when the trade-off between distance and coverage is being calculated. Three kinds of heuristic algorithms are developed. First, local search procedures are designed both for constructing and improving feasible solutions. Second, a multistart GRASP heuristic is developed, based on the previous local search methods. Third, by employing Lagrangean relaxation methods, a very efficient Lagrangean heuristic algorithm is designed, which extends the well known algorithm of Handler and Zang, for constrained shortest path problems, to constrained p-median problems. Finally, a comparison of the computational efficiency of the developed methods is made between a variety of problems of different sizes.

Suggested Citation

  • Sáez-Aguado, Jesús & Trandafir, Paula Camelia, 2012. "Some heuristic methods for solving p-median problems with a coverage constraint," European Journal of Operational Research, Elsevier, vol. 220(2), pages 320-327.
    • Handle: RePEc:eee:ejores:v:220:y:2012:i:2:p:320-327
    DOI: 10.1016/j.ejor.2012.02.011
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    Cited by:

    1. Jianing Zhi & Burcu B. Keskin, 2018. "A Multi-Product Production/Distribution System Design Problem with Direct Shipments and Lateral Transshipments," Networks and Spatial Economics, Springer, vol. 18(4), pages 937-972, December.
    2. Jesús Sáez-Aguado & Paula Camelia Trandafir, 2018. "Variants of the $$ \varepsilon $$ ε -constraint method for biobjective integer programming problems: application to p-median-cover problems," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 87(2), pages 251-283, April.
    3. Santi, Éverton & Aloise, Daniel & Blanchard, Simon J., 2016. "A model for clustering data from heterogeneous dissimilarities," European Journal of Operational Research, Elsevier, vol. 253(3), pages 659-672.

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