Benchmarking RM-MEDA on the Bi-objective BBOB-2016 Test Suite - Université de Lille Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Benchmarking RM-MEDA on the Bi-objective BBOB-2016 Test Suite

Résumé

In this paper, we benchmark the Regularity Model-Based Multiobjective Estimation of Distribution Algorithm (RM-MEDA) of Zhang et al. on the bi-objective bbob-biobj test suite of the Comparing Continuous Optimizers (COCO) platform. It turns out that, starting from about 200 times dimension many function evaluations, RM-MEDA shows a linear increase in the solved hypervolume-based target values with time until a stagnation of the performance occurs rather quickly on all problems. The final percentage of solved hy-pervolume targets seems to decrease with the problem dimension .
Fichier principal
Vignette du fichier
wk0810-auger-RM-MEDA-authorversion.pdf (4.52 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01435449 , version 1 (14-01-2017)

Identifiants

Citer

Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Dejan Tušar, Tea Tušar, et al.. Benchmarking RM-MEDA on the Bi-objective BBOB-2016 Test Suite. GECCO 2016 - Genetic and Evolutionary Computation Conference, Jul 2016, Denver, CO, United States. pp.1241-1247, ⟨10.1145/2908961.2931707⟩. ⟨hal-01435449⟩
512 Consultations
147 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More