Multi-type maximal covering location problems: Hybridizing discrete and continuous problems

This paper introduces a general modeling framework for multi-type maximal covering location problem in which the position of facilities different normed spaces are simultaneously decided to maximize demand generated by set points. From need intertwining decisions discrete and continuous sets, hybridized is considered some types be located finite sets others spaces. A natural non-linear model proposed an integer linear programming reformulation derived. branch-and-cut algorithm developed better tackling problem. The study proceeds considering particular case Euclidean plane. In this case, taking advantage from geometrical properties it possible propose alternative model. results extensive battery computational experiments performed assess methodological contribution work reported. Apart synthetic dataset, approaches tested on real geographical demographic data with up 920 nodes.