On the impact of a small initial population size in the IPOP active CMA-ES with mirrored mutations on the noiseless BBOB testbed

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Abstract

Active Covariance Matrix Adaptation and Mirrored Mutations have been independently proposed as improved variants of the well-known optimization algorithm Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for numerical optimization. This paper investigates the impact of the algorithm's population size when both active covariance matrix adaptation and mirrored mutation are used in the CMA-ES. To this end, we compare the CMA-ES with standard population size λ, i.e., λ = 4+⌊3 log(D) ⌋ with a version with half this population size where D is the problem dimension.

Original languageEnglish
Title of host publicationGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion
PublisherAssociation for Computing Machinery
Pages285-290
Number of pages6
ISBN (Print)9781450311786
DOIs
Publication statusPublished - 1 Jan 2012
Event14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion - Philadelphia, PA, United States
Duration: 7 Jul 201211 Jul 2012

Publication series

NameGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion

Conference

Conference14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion
Country/TerritoryUnited States
CityPhiladelphia, PA
Period7/07/1211/07/12

Keywords

  • Benchmarking
  • Black-box optimization

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