A Basic Variable Neighborhood Search for the Planar Obnoxious Facility Location Problem

Abstract

Obnoxious facility location problems are devoted to choose the best location for a given set of facilities considering that, despite they should not be close to population communities, their service is needed, like the case of airports, paper factories or nuclear plants. In this paper we study the planar multiple obnoxious facility location problem. Our approach is based on a first discretization of the instance where a Basic Variable Neighborhood Search algorithm is applied. Our results improve the state of the art spending less than a third of the execution time of the second best algorithm.

Sergio Salazar

Artificial Intelligence Phd Student

Sergio Salazar graduated in Mathematics and Computer Science from the Rey Juan Carlos University in 2023. He is working here as a predoctoral researcher focusing in Continious Facilities Location Problems.

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.

J. Manuel Colmenar

Full Professor

My research interests are focused on metaheuristics applied to optimization problems. I have worked on different combinatorial optimization problems applying trajectorial algorithms such us GRASP or VNS. Besides, I am very interested in applications of Grammatical Evolution, specifically in model and prediction domain, as alternative to machine learning approaches.