Abstract
An entering firm wants to compete for market share in a given area by opening some new facilities selected among a finite set of potential locations. Customers are spatially separated and other firms are already operating in that area. In this paper, we analyse the effect of two different customers’ behavior over the optimal solutions, the Huff and the Pareto-Huff customer choice rules. In the first, the customer splits its demand among all competing facilities according to its attractions. In the second, the customer splits its demand among the facilities that are Pareto optimal with respect to the attraction (to be maximized) and the distance (to be minimized), proportionally to their attractions. So, a competitive facility location problem on discrete space is considered in which an entering firm wants to locate a fixed number of new facilities for market share maximization when both Huff and Pareto-Huff customer behavior are used. In order to solve these two models, a heuristic procedure is proposed to obtain the best solutions, and it is compared with a classical genetic algorithm for a set of real geographical coordinates and population data of municipalities in Spain.
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Acknowledgments
This research has been supported by the Ministry of Economy and Competitiveness of Spain under the research project MTM2015-70260-P, and the Fundación Séneca (The Agency of Science and Technology of the Region of Murcia) under the research project 19241/PI/14, and also by a grant (No. MIP-051/2014) from the Research Council of Lithuania.
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Fernández, P., Pelegrín, B., Lančinskas, A., Žilinskas, J. (2018). The Huff Versus the Pareto-Huff Customer Choice Rules in a Discrete Competitive Location Model. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10961. Springer, Cham. https://doi.org/10.1007/978-3-319-95165-2_41
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DOI: https://doi.org/10.1007/978-3-319-95165-2_41
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