BBOB: Nelder-Mead with Resize and Halfruns

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Using the BBOB template, we investigate how the Nelder-Mead simplex algorithm can be combined with evolutionary ideas to give a competitive hybrid approach to optimize continuous functions. We significantly improve the performance of the algorithm in higher dimension by the addition of a reshaping step of the search, to correct for a known problem in the simplex search behaviour. We also give a reasonably good population-based approach in which only a third of the individuals is fully matured, with a bias towards fitter individuals, via a variant of the Nelder-Mead method.

Original languageEnglish
Title of host publicationProceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
PublisherAssociation for Computing Machinery
Pages2239-2245
Number of pages7
ISBN (Print)9781605583259
DOIs
Publication statusPublished - 1 Jan 2009
Externally publishedYes
Event11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 - Montreal, QC, Canada
Duration: 8 Jul 200912 Jul 2009

Publication series

NameProceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Volume2009-January

Conference

Conference11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Country/TerritoryCanada
CityMontreal, QC
Period8/07/0912/07/09

Keywords

  • benchmarking
  • black-box optimization
  • evolutionary computation

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