Benchmarking CMAES-APOP on the BBOB noiseless testbed

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Abstract

In this paper, we investigate a new approach for adapting population size in the CMA-ES. .is method is based on tracking the information in each slot of S successive iterations to decide whether we should increase or decrease or keep the population size in the next slot of S iterations. .e information which we collect is the non-decrease of the median of the objective function values. We will show the efficiency of our approach on some multi-modal functions with adequate global structure.

Original languageEnglish
Title of host publicationGECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages1756-1763
Number of pages8
ISBN (Electronic)9781450349390
DOIs
Publication statusPublished - 15 Jul 2017
Event2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017 - Berlin, Germany
Duration: 15 Jul 201719 Jul 2017

Publication series

NameGECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference Companion

Conference

Conference2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017
Country/TerritoryGermany
CityBerlin
Period15/07/1719/07/17

Keywords

  • Benchmarking
  • Black-box optimization
  • CMA-ES
  • Evolutionary computation
  • Popsize Adaptation

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