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Computational Results for an Automatically Tuned CMA-ES withIncreasing Population Size on the CEC'05 Benchmark Set

par Liao, Tianjun ;Montes De Oca Roldan, Marco ;Stützle, Thomas
Référence Soft Computing, 17, 6, page (1031-1046)
Publication Publié, 2013-06

Article révisé par les pairs

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Résumé :

In this article, we apply an automatic algorithm configuration tool to improve the performance of the CMA-ES algorithm with increasing population size (iCMA-ES), the best performing algorithm on the CEC'05 benchmark set for continuous function optimization. In particular, we consider a separation between tuning and test sets and, thus, tune iCMA-ES on a different set of functions than the ones of the CEC'05 benchmark set. Our experimental results show that the tuned iCMA-ES improves significantly over the default version of iCMA-ES. Furthermore, we provide some further analyses on the impact of the modified parameter settings on iCMA-ES performance and a comparison with recent results of algorithms that use CMA-ES as a subordinate local search. © 2012 Springer-Verlag Berlin Heidelberg.