Multitype Maximal Covering Location Problems: Hybridizing discrete and continuous problems Blanco Izquierdo, Víctor Gázquez, Ricardo Saldanha-da-Gama, Francisco Acknowledgements This research has been partially supported by Spanish Ministerio de Ciencia e Innovación, AEI/FEDER grant number PID2020-114594GBC21, Junta de Andalucía projects P18-FR- 1422/2369 and projects FEDERUS-1256951, B-FQM-322-UGR20, CEI-3-FQM331 and Netmeet- Data (Fundación BBVA 2019). The first author was also partially supported by the IMAG-Maria de Maeztu grant CEX2020-001105-M /AEI /10.13039/501100011033. The second author was partially supported by Spanish Ministry of Education and Science grant number PEJ2018- 002962-A, the PhD Program in Mathematics at the Universidad de Granada and Becas de Movilidad entre Universidades Andaluzas e Iberoamericanas (AUIP). The third author was partially funded by grant UIDB/04561/2020 from National Funding from FCT|Fundaçao para a Ciencia e Tecnologia, Portugal. This paper introduces a general modeling framework for a multi-type maximal covering location problem in which the position of facilities in different metric spaces are simultaneously decided to maximize the demand generated by a set of points. From the need of intertwining location decisions in discrete and in continuous sets, a general hybridized problem is considered in which some types of facilities are to be located in finite sets and the others in continuous metric spaces. A natural non-linear model is proposed for which an integer linear programming reformulation is derived. A branch-and-cut algorithm is developed for better tackling the problem. The study proceeds considering the particular case in which the continuous facilities are to be located in the Euclidean plane. In this case, taking advantage from some geometrical properties it is possible to propose an alternative integer linear programming model. The results of an extensive battery of computational experiments performed to assess the methodological contribution of this work is reported on. The data consists of up to 920 demand nodes using real geographical and demographic data. 2022-12-12T13:18:59Z 2022-12-12T13:18:59Z 2021-11-29 journal article ARTICLE IN PRESS: V. Blanco, R. Gázquez and F. Saldanha-da-Gama. Multitype Maximal Covering Location Problems: Hybridizing discrete and continuous problems. European Journal of Operational Research xxx (xxxx) xxx: [https://doi.org/10.1016/j.ejor.2022.10.037] https://hdl.handle.net/10481/78402 10.1016/j.ejor.2022.10.037 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional