Closed state model for understanding the dynamics of MOEAs

Monzón, Hugo; Aguirre, Hernan; Verel, Sébastien; Liefooghe, Arnaud; Derbel, Bilel; Tanaka, Kiyoshi

Type de document :

Communication dans un congrès avec actes

Titre :

Closed state model for understanding the dynamics of MOEAs

Auteur(s) :

Monzón, Hugo [Auteur]
Faculty of Engineering [Nagano]
Aguirre, Hernan [Auteur]
Faculty of Engineering [Nagano]
Verel, Sébastien [Auteur]
Laboratoire d'Informatique Signal et Image de la Côte d'Opale [LISIC]
Liefooghe, Arnaud [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Derbel, Bilel [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Tanaka, Kiyoshi [Auteur]
Faculty of Engineering [Nagano]

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

Peter A. N. Bosman

Titre de la manifestation scientifique :

Genetic and Evolutionary Computation Conference (GECCO 2017)

Ville :

Berlin

Pays :

Allemagne

Date de début de la manifestation scientifique :

2017-07-15

Titre de l’ouvrage :

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference

Éditeur :

Association for Computing Machinery (ACM)

Date de publication :

2017-07-01

Discipline(s) HAL :

Informatique [cs]/Intelligence artificielle [cs.AI]

Résumé en anglais : [en]

This work proposes the use of simple closed state models to capture, analyze and compare the dynamics of multi- and many-objective evolutionary algorithms. Two- and three-state models representing the composition of the ...
Lire la suite >This work proposes the use of simple closed state models to capture, analyze and compare the dynamics of multi- and many-objective evolutionary algorithms. Two- and three-state models representing the composition of the instantaneous population are described and learned for representatives of the major approaches to multi-objective optimization, i.e. dominance, extensions of dominance, decomposition, and indicator algorithms. The model parameters are trained from data obtained running the algorithms with various population sizes on enumerable MNK-landscapes with 3, 4, 5 and 6 objectives. We show ways to interpret and use the model parameter values in order to analyze the population dynamics according to selected features. For example, we are interested in knowing how parameter values change for a given population size with the increase of the number of objectives. We also show a graphical representation capturing in one graph how the parameters magnitude and sign relate to the connections between states.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

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