Titre :

Geometric Differential Evolution in MOEA/D: A Preliminary Study

Auteur(s) :

Zapotecas-Martínez, Saúl [Auteur]
Faculty of Engineering [Nagano]
Derbel, Bilel [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Liefooghe, Arnaud [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Aguirre, Hernan [Auteur]
Faculty of Engineering [Nagano]
Tanaka, Kiyoshi [Auteur]
Faculty of Engineering [Nagano]

Éditeur(s) ou directeur(s) scientifique(s) :

Springer

Titre de la manifestation scientifique :

The 14th LNCS-LNAI International Conference on Artificial Intelligence (MICAI)

Ville :

Cuernavaca

Pays :

Mexique

Date de début de la manifestation scientifique :

2015-10-25

Titre de la revue :

The 14th LNCS-LNAI International Conference on Artificial Intelligence (MICAI)

Éditeur :

Springer

Date de publication :

2015-10-25

Discipline(s) HAL :

Computer Science [cs]/Operations Research [math.OC]
Mathématiques [math]/Combinatoire [math.CO]
Mathématiques [math]/Optimisation et contrôle [math.OC]

Résumé en anglais : [en]

The multi-objective evolutionary algorithm based on decomposition (MOEA/D) is an aggregation-based algorithm which has became successful for solving multi-objective optimization problems (MOPs).So far, for the continuous ...
Lire la suite >The multi-objective evolutionary algorithm based on decomposition (MOEA/D) is an aggregation-based algorithm which has became successful for solving multi-objective optimization problems (MOPs).So far, for the continuous domain, the most successful variants of MOEA/D are based on differential evolution (DE) operators. However, no investigations on the application of DE-like operators within MOEA/D exist in the context of combinatorial optimization. This is precisely the focus of the work reported in this paper. More particularly, we study the incorporation of geometric differential evolution (gDE), the discrete generalization of DE, into the MOEA/D framework.We conduct preliminary experiments in order to study the effectiveness of gDE when coupled with MOEA/D. Our results indicate that the proposed approach is highly competitive with respect to the original version of MOEA/D, when solving a combinatorial optimization problem having between two and four objective functions.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL