A Cultural Algorithm Applied in a Bi-Objective Uncapacitated Facility Location Problem

Cultural Algorithms (CAs) are one of the metaheuristics which can adapt in order to work in multi-objectives optimization environments. On the other hand, Bi-Objective Uncapacitated Facility Location Problem (BOUFLP) and particularly Uncapacitated Facility Location Problem (UFLP) are a well know problems in literature. However, a few articles have worked in the sense of applied evolutionary multiobjective (EMO) algorithms to these problem and we do not find articles where CAs were applied to the BOUFLP. In this article we presents a Bi-Objective Cultural Algorithm (BOCA) which was applied to the BiObjective Uncapacitated Facility Location Problem (BOUFLP) and it obtain an important improves in comparison with other well-know EMO algorithms as PAES and NSGA-II. The criterion which was considered in this work was both, cost (in order to minimize it) and coverage (in order to maximize it). The different solutions obtained with the CA were compared using an S metric proposed in [1] and used in several works in the literature.