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Heuristic Solutions to the Facility Location Problem with General Bernoulli Demands

Author

Listed:
  • Maria Albareda-Sambola

    (Universitat Politècnica de Catalunya, Departament d’Estadística i Investigació Operativa, 08222 Terrassa, Spain)

  • Elena Fernández

    (Universitat Politècnica de Catalunya, Departament d’Estadística i Investigació Operativa, 08034 Barcelona, Spain; Barcelona Graduate School of Mathematics (BGSMath), 08193 Bellaterra, Barcelona, Spain)

  • Francisco Saldanha-da-Gama

    (Universidade de Lisboa, Faculdade de Ciências, Departamento de Estatística e Investigação Operacional e Centro de Matemática, Aplicações Fundamentais e Investigação Operacional, 1749-016 Lisboa, Portugal)

Abstract

In this paper, a heuristic procedure is proposed for the facility location problem with general Bernoulli demands. This is a discrete facility location problem with stochastic demands that can be formulated as a two-stage stochastic program with recourse. In particular, facility locations and customer assignments must be decided here and now, i.e., before knowing the customers who will actually require to be served. In a second stage, service decisions are made according to the actual requests. The heuristic proposed consists of a greedy randomized adaptive search procedure followed by a path relinking. The heterogeneous Bernoulli demands make prohibitive the computational effort for evaluating feasible solutions. Thus the expected cost of a feasible solution is simulated when necessary. The results of extensive computational tests performed for evaluating the quality of the heuristic are reported, showing that high-quality feasible solutions can be obtained for the problem in fairly small computational times.

Suggested Citation

  • Maria Albareda-Sambola & Elena Fernández & Francisco Saldanha-da-Gama, 2017. "Heuristic Solutions to the Facility Location Problem with General Bernoulli Demands," INFORMS Journal on Computing, INFORMS, vol. 29(4), pages 737-753, November.
  • Handle: RePEc:inm:orijoc:v:29:y:2017:i:4:p:737-753
    DOI: 10.1287/ijoc.2017.0755
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    References listed on IDEAS

    as
    1. Isabel Correia & Francisco Saldanha Gama, 2015. "Facility Location Under Uncertainty," Springer Books, in: Gilbert Laporte & Stefan Nickel & Francisco Saldanha da Gama (ed.), Location Science, edition 127, chapter 0, pages 177-203, Springer.
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    4. Mauricio G.C. Resende & Celso C. Ribeiro, 2010. "Greedy Randomized Adaptive Search Procedures: Advances, Hybridizations, and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 283-319, Springer.
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    6. Manuel Laguna & Rafael Marti, 1999. "GRASP and Path Relinking for 2-Layer Straight Line Crossing Minimization," INFORMS Journal on Computing, INFORMS, vol. 11(1), pages 44-52, February.
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    8. Cattaruzza, Diego & Absi, Nabil & Feillet, Dominique & Vidal, Thibaut, 2014. "A memetic algorithm for the Multi Trip Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 236(3), pages 833-848.
    9. Albareda-Sambola, Maria & Fernández, Elena & Saldanha-da-Gama, Francisco, 2011. "The facility location problem with Bernoulli demands," Omega, Elsevier, vol. 39(3), pages 335-345, June.
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    Cited by:

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    2. Sen Lin & Bo Li & Antonio Arreola-Risa & Yiwei Huang, 2023. "Optimizing a single-product production-inventory system under constant absolute risk aversion," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 510-537, October.
    3. Yang Wang & Yumeng Zhang & Mengyu Bi & Jianhui Lai & Yanyan Chen, 2022. "A Robust Optimization Method for Location Selection of Parcel Lockers under Uncertain Demands," Mathematics, MDPI, vol. 10(22), pages 1-15, November.

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