CMA-ES with Restarts for Solving CEC 2013 Benchmark Problems

Ilya Loshchilov 1
1 Laboratory of Intelligent Systems (LIS)
LIS - Laboratory of Intelligent Systems
Abstract : This paper investigates the performance of 6 versions of Covariance Matrix Adaptation Evolution Strategy (CMA-ES) with restarts on a set of 28 noiseless optimization problems (including 23 multi-modal ones) designed for the special session on real-parameter optimization of CEC 2013. The experimental validation of the restart strategies shows that: i). the versions of CMA-ES with weighted active covariance matrix update outperform the original versions of CMA-ES, especially on ill-conditioned problems; ii). the original restart strategies with increasing population size (IPOP) are usually outperformed by the bi-population restart strategies where the initial mutation step-size is also varied; iii). the recently proposed alternative restart strategies for CMA-ES demonstrate a competitive performance and are ranked first w.r.t. the proportion of function-target pairs solved after the full run on all 10-, 30- and 50-dimensional problems.
Type de document :
Communication dans un congrès
IEEE Congress on Evolutionary Computation, Jun 2013, Cancun, Mexico. 2013
Liste complète des métadonnées

https://hal.inria.fr/hal-00823880
Contributeur : Loshchilov Ilya <>
Soumis le : samedi 18 mai 2013 - 20:06:01
Dernière modification le : lundi 13 octobre 2014 - 15:43:25
Document(s) archivé(s) le : lundi 19 août 2013 - 05:00:50

Fichiers

CEC2013.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00823880, version 1

Citation

Ilya Loshchilov. CMA-ES with Restarts for Solving CEC 2013 Benchmark Problems. IEEE Congress on Evolutionary Computation, Jun 2013, Cancun, Mexico. 2013. 〈hal-00823880〉

Partager

Métriques

Consultations de la notice

173

Téléchargements de fichiers

378