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Discrete Competitive Facility Location by Ranking Candidate Locations

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Data Science: New Issues, Challenges and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 869))

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Abstract

Competitive facility location is a strategic decision for firms providing goods or services and competing for the market share in a geographical area. There are different facility location models and solution procedures proposed in the literature which vary on their ingredients, such as location space, customer behavior, objective function(s), etc. In this paper we focus on two discrete competitive facility location problems: a single objective discrete facility location problem for an entering firm and a bi-objective discrete facility location problem for firm expansion. Two random search algorithms for discrete facility location based on ranking of candidate locations are described and the results of their performance investigation are discussed. It is shown that the ranking of candidate locations is a suitable strategy for discrete facility location as the algorithms are able to determine the optimal solution for different instances of the facility location problem or approximate the optimal solution with a reasonable accuracy.

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Acknowledgements

This research has been supported by Fundación Séneca (The Agency of Science and Technology of the Region of Murcia, Spain) under the research project 20817/PI/18. This article is based upon work from COST Action CA15140 “Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO)” supported by COST (European Cooperation in Science and Technology).

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Authors and Affiliations

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

    Algirdas Lančinskas & Julius Žilinskas

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

    Pascual Fernández & Blas Pelegrín

Authors
  1. Algirdas Lančinskas
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  2. Pascual Fernández
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  3. Blas Pelegrín
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  4. Julius Žilinskas
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Corresponding author

Correspondence to Algirdas Lančinskas .

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Editors and Affiliations

  1. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

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

    Jolita Bernatavičienė

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Lančinskas, A., Fernández, P., Pelegrín, B., Žilinskas, J. (2020). Discrete Competitive Facility Location by Ranking Candidate Locations. In: Dzemyda, G., Bernatavičienė, J., Kacprzyk, J. (eds) Data Science: New Issues, Challenges and Applications. Studies in Computational Intelligence, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-39250-5_8

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