Abstract
This paper introduces a route-planning problem with applications in tourism. The goal of the Tourist Trip Design Problem is to maximize the number of points of interest to visit. We propose a new variant, in our view more realistic, where on the one hand, the points of interest are clustered in various categories and on the other, the scores and travel time constraints are fuzzy. In this work time constraints are modeled as fuzzy. A fuzzy optimization approach and an efficient greedy randomized adaptive search procedure are applied to solve the problem. The computational experiments indicate that this soft computing approach is able to find significant solutions.
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Acknowledgements
This work has been partially funded by the Spanish Ministry of Economy and Competitiveness with FEDER funds (TIN2015-70226-R) and supported by Fundación Cajacanarias research funds (project 2016TUR19) and the iMODA Network of the AUIP. Contributions from Airam Expósito-Márquez is supported by la Agencia Canaria de Investigación, Innovación y Sociedad de la Información de la Consejería de Economía, Industria, Comercio y Conocimiento and by the Fondo Social Europeo (FSE).
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Expósito, A., Mancini, S., Brito, J., Moreno, J.A. (2019). Solving a Fuzzy Tourist Trip Design Problem with Clustered Points of Interest. In: Bello, R., Falcon, R., Verdegay, J. (eds) Uncertainty Management with Fuzzy and Rough Sets. Studies in Fuzziness and Soft Computing, vol 377. Springer, Cham. https://doi.org/10.1007/978-3-030-10463-4_2
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