A preference-based multi-objective evolutionary algorithm for approximating a region of interest

Abstract

Multi-objective preference-based evolutionary algorithms approximate the part of the Pareto front that meets the preference information expressed by the Decision Maker. However, only a few of such algorithms are able to obtain well-distributed solutions covering the complete “region of interest”. In this work a preference-based evolutionary algorithm for approximating the region of interest of multi-objective optimization problems is proposed. The efficiency of the proposed algorithm has been experimentally evaluated and compared to another state-of-the-art multi-objective preference- based evolutionary algorithm by solving a set of multi-objective optimization benchmark problems.