Iterated Local Search for the Facility Location Problem with Limited Choice Rule

Abstract

Facility location problems cover a great variety of different real-life scenarios. Among them, it is usual to consider distances between facilities and/or distances with clients in order to determine the best location for them. However, a different problem arises when the distribution of clients among the open facilities is considered and the cost of opening the facilities is also taken into account. In this paper, we study a problem with these features, the Facility Location problem with Limited Choice rule. We propose a first metaheuristic approach to this problem by means of an Iterated Local Search, which is able to obtain similar results than the state of the art spending shorter execution times.

Publication
Advances in Artificial Intelligence
Enrique García Galán
Enrique García Galán
Artificial Intelligence Phd Student

Always learning, searching for knowledge to improve in every possible aspect. Working on my Ph.D. while working at Telefonica.

Alberto Herrán González
Alberto Herrán González
Associate Professor
J. Manuel Colmenar
J. Manuel Colmenar
Associate 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.