An Efficient Fixed Set Search for the Covering Location with Interconnected Facilities Problem

Abstract

This paper studies the Coverage Location Problem with Interconnected Facilities (CPIF). It belongs to the family of Facility Location Problems, but being more realistic to nowadays situations as surveillance, or natural disaster control. This problem aims at locating a set of interconnected facilities to minimize the number of demand points that are not covered by the selected facilities. Two facilities are considered as interconnected if the distance between them is smaller than or equal to a predefined distance, while a facility covers a demand point if the distance to it is smaller than a certain threshold. The wide variety of real-world applications that fit into this model makes them attractive for designing an algorithm able to solve the problem efficiently. To this end, a metaheuristic algorithm based on the Fixed Set Search framework is implemented. The proposed algorithm will be able to provide high-quality solutions in short computational times, being competitive with the state-of-the-art.

Isaac Lozano-Osorio

Phd in Artificial Intelligence

Isaac Lozano graduated with a double degree in Computer Engineering and Computer Engineering from the Universidad Rey Juan Carlos, where he was awarded the prize for the Best Final Project. Subsequently, he completed a Master in Artificial Intelligence Research (UIMP). His main research interests are focused on the interface between Computer Science, Artificial Intelligence and Operations Research. Most of his publications deal with the development of metaheuristic procedures for graph modeled optimization problems.

Jesús Sánchez-Oro

Associate Professor

Associate Professor at the Computer Science Department, being one of the senior researchers of the Group for Research on Algorithms For Optimization GRAFO.

Abraham Duarte

Full Professor

Abraham Duarte is Full Professor in the Computer Science Department at the Rey Juan Carlos University (Madrid, Spain). He has done extensive research in the interface between computer science, artificial intelligence, and operations research to develop solution methods based on Computational Intelligence (metaheuristics) for practical problems in operations-management areas such as logistics and supply chains, telecommunications, decision-making under uncertainty and optimization of simulated systems.