In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
— Hypervolume based multiobjective evolutionary algorithms (MOEA) nowadays seem to be the first choice when handling multiobjective optimization problems with many, i.e., at lea...
In this paper we propose to use a distance metric based on user-preferences to efficiently find solutions for many-objective problems. In a user-preference based algorithm a decis...
Abstract. We describe EDRL-MD, an evolutionary algorithm-based system, for learning decision rules from databases. The main novelty of our approach lies in dealing with continuous ...