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Black-Box Optimization Benchmarking the IPOP-CMA-ES on the Noiseless Testbed

Raymond Ros 1
1 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : We benchmark the Covariance Matrix Adaptation-Evolution Strategy (CMA-ES) algorithm with an Increasing POPulation size (IPOP) restart policy on the BBOB noiseless testbed. The IPOP-CMA-ES is compared to the BIPOP-CMA-ES and is shown to perform at best two times faster on multi-modal functions f15 to f19 whereas it does not solve weakly structured functions f22, f23 and f24.
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https://hal.inria.fr/inria-00473777
Contributor : Raymond Ros <>
Submitted on : Friday, April 16, 2010 - 2:05:47 PM
Last modification on : Tuesday, April 21, 2020 - 1:07:13 AM
Document(s) archivé(s) le : Tuesday, September 28, 2010 - 12:41:05 PM

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  • HAL Id : inria-00473777, version 1

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Raymond Ros. Black-Box Optimization Benchmarking the IPOP-CMA-ES on the Noiseless Testbed. Genetic and Evolutionary Computation Conference 2010, Jul 2010, Portland, OR, United States. ⟨inria-00473777⟩

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