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On the fuzzy maximal covering location problem

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  • Arana-Jiménez, Manuel
  • Blanco, Víctor
  • Fernández, Elena

Abstract

This paper studies the maximal covering location problem, assuming imprecise knowledge of all data involved. The considered problem is modeled from a fuzzy perspective producing suitable fuzzy Pareto solutions. Some properties of the fuzzy model are studied, which validate the equivalent mixed-binary linear multiobjective formulation proposed. A solution algorithm is developed, based on the augmented weighted Tchebycheff method, which produces solutions of guaranteed Pareto optimality. The effectiveness of the algorithm has been tested with a series of computational experiments, whose numerical results are presented and analyzed.

Suggested Citation

  • Arana-Jiménez, Manuel & Blanco, Víctor & Fernández, Elena, 2020. "On the fuzzy maximal covering location problem," European Journal of Operational Research, Elsevier, vol. 283(2), pages 692-705.
    • Handle: RePEc:eee:ejores:v:283:y:2020:i:2:p:692-705
    DOI: 10.1016/j.ejor.2019.11.036
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    References listed on IDEAS

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    1. Izaz Ullah Khan & Tahir Ahmad & Normah Maan, 2013. "A Simplified Novel Technique for Solving Fully Fuzzy Linear Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 159(2), pages 536-546, November.
    2. Herrera, F. & Verdegay, J. L., 1995. "Three models of fuzzy integer linear programming," European Journal of Operational Research, Elsevier, vol. 83(3), pages 581-593, June.
    3. Berman, Oded & Krass, Dmitry & Drezner, Zvi, 2003. "The gradual covering decay location problem on a network," European Journal of Operational Research, Elsevier, vol. 151(3), pages 474-480, December.
    4. Richard Church & Charles R. Velle, 1974. "The Maximal Covering Location Problem," Papers in Regional Science, Wiley Blackwell, vol. 32(1), pages 101-118, January.
    5. CONSTANTINE TOREGAS & CHARLES ReVELLE, 1972. "Optimal Location Under Time Or Distance Constraints," Papers in Regional Science, Wiley Blackwell, vol. 28(1), pages 133-144, January.
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    Cited by:

    1. Diehlmann, Florian & Klein, Miriam & Wiens, Marcus & Lüttenberg, Markus & Schultmann, Frank, 2020. "On the value of accurate demand information in public-private emergency collaborations," Working Paper Series in Production and Energy 51, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    2. Blanco, Víctor & Gázquez, Ricardo & Saldanha-da-Gama, Francisco, 2023. "Multi-type maximal covering location problems: Hybridizing discrete and continuous problems," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1040-1054.
    3. Baldomero-Naranjo, Marta & Kalcsics, Jörg & Marín, Alfredo & Rodríguez-Chía, Antonio M., 2022. "Upgrading edges in the maximal covering location problem," European Journal of Operational Research, Elsevier, vol. 303(1), pages 14-36.
    4. Chen, Liang & Chen, Sheng-Jie & Chen, Wei-Kun & Dai, Yu-Hong & Quan, Tao & Chen, Juan, 2023. "Efficient presolving methods for solving maximal covering and partial set covering location problems," European Journal of Operational Research, Elsevier, vol. 311(1), pages 73-87.
    5. Diana Puspita Sari & Nur Aini Masruroh & Anna Maria Sri Asih, 2021. "Extended Maximal Covering Location and Vehicle Routing Problems in Designing Smartphone Waste Collection Channels: A Case Study of Yogyakarta Province, Indonesia," Sustainability, MDPI, vol. 13(16), pages 1-23, August.

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