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A discrete competitive facility location model with proportional and binary rules sequentially applied

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Abstract

The paper is focused on discrete competitive facility location problem for an entering firm considering different customer behavior models: for essential goods, customers generally spread their buying power among all facilities within an attraction area, but if there are no facilities nearby, then customers choose a single highly attractive facility outside the attraction area to satisfy their demand. The new facility location model has been proposed considering the proportional customer choice rule for customers with facilities within the attraction area and the binary rule—for customers which facilities are located outside the attraction area. The model has been formulated as a non-linear binary programming problem and a heuristic optimization algorithm has been applied to find the optimal solutions for different instances of the problem using real geographical coordinates and population data of thousands of municipalities in Spain.

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Data Availibility

The datasets analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This research has been supported by the Fundación Séneca (The Agency of Science and Technology of the Region of Murcia) under the research project 20817/PI/18.

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Authors and Affiliations

  1. Department of Statistics and Operations Research, University of Murcia, Campus Espinardo, 30071, Murcia, Spain

    Pascual Fernández, Blas Pelegrín & Julius Žilinskas

  2. Institute of Data Science and Digital Technologies, Vilnius University, Akademijos 4, 08412, Vilnius, Lithuania

    Algirdas Lančinskas

Authors
  1. Pascual Fernández
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  2. Algirdas Lančinskas
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  3. Blas Pelegrín
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  4. Julius Žilinskas
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Correspondence to Algirdas Lančinskas.

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Fernández, P., Lančinskas, A., Pelegrín, B. et al. A discrete competitive facility location model with proportional and binary rules sequentially applied. Optim Lett 17, 867–877 (2023). https://doi.org/10.1007/s11590-022-01938-x

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  • DOI: https://doi.org/10.1007/s11590-022-01938-x

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