Solution of asymmetric discrete competitive facility location problems using ranking of candidate locations

Abstract

We address a discrete competitive facility location problem with an asymmetric objective function and a binary customer choice rule. Both an integer linear programming formulation and a heuristic optimization algorithm based on ranking of candidate locations are designed to solve the problem. The proposed population-based heuristic algorithm is specially adapted for the discrete facility location problems by using their features such as geographical distances and the maximal possible utility of candidate locations, which can be evaluated in advance. The performance of the proposed algorithm was experimentally investigated by solving different instances of the model with real data of municipalities in Spain.

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Acknowledgements

This research is funded by the European Social Fund under the No. 09.3.3-LMT-K-712 “Development of Competences of Scientists, other Researchers and Students through Practical Research Activities” measure. This research is funded by the Ministry of Economy and Competitiveness of Spain under the research Project MTM2015-70260-P, and by the Fundación Séneca (The Agency of Science and Technology of the Region of Murcia) under the research Project 19241/PI/14.

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Correspondence to Algirdas Lančinskas.

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Lančinskas, A., Žilinskas, J., Fernández, P. et al. Solution of asymmetric discrete competitive facility location problems using ranking of candidate locations. Soft Comput (2020). https://doi.org/10.1007/s00500-020-05106-0

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Keywords

  • Asymmetric facility location
  • Binary choice rule
  • Combinatorial optimization
  • Random search
  • Population-based heuristic algorithms