Approximating the pareto-front of continuous bi-objective problems: Application to a competitive facility location problem

Abstract

A new general multi-objective optimization heuristic algorithm, suitable for being applied to continuous multi-objective optimization problems is proposed. It deals with the problem at hand in a fast and efficient way. It combines ideas from different multi-objective and single-objective optimization evolutionary algorithms, although it also incorporates new devices which help to reduce the computational requirements, and also to improve the quality of the provided solutions. To show its applicability, a bi-objective competitive facility location and design problem is considered. This problem has been previously tackled through exact general methods, but they require high computational effort. A comprehensive computational study shows that the heuristic method is competitive, being able to reduce, in average, the computing time of the exact method by approximately 98%, and offering good quality in the final solutions. © 2012 Springer-Verlag.