Does comma selection help to cope with local optima?

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Abstract

One hope of using non-elitism in evolutionary computation is that it aids leaving local optima. We perform a rigorous runtime analysis of a basic non-elitist evolutionary algorithm (EA), the (μ, λ) EA, on the most basic benchmark function with a local optimum, the jump function. We prove that for all reasonable values of the parameters and the problem, the expected runtime of the (μ, λ) EA is, apart from lower order terms, at least as large as the expected runtime of its elitist counterpart, the (μ + λ) EA (for which we conduct the first runtime analysis to allow this comparison). Consequently, the ability of the (μ, λ) EA to leave local optima to inferior solutions does not lead to a runtime advantage. We complement this lower bound with an upper bound that, for broad ranges of the parameters, is identical to our lower bound apart from lower order terms. This is the first runtime result for a non-elitist algorithm on a multi-modal problem that is tight apart from lower order terms.

Original languageEnglish
Title of host publicationGECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery
Pages1304-1313
Number of pages10
ISBN (Electronic)9781450371285
DOIs
Publication statusPublished - 25 Jun 2020
Event2020 Genetic and Evolutionary Computation Conference, GECCO 2020 - Cancun, Mexico
Duration: 8 Jul 202012 Jul 2020

Publication series

NameGECCO 2020 - Proceedings of the 2020 Genetic and Evolutionary Computation Conference

Conference

Conference2020 Genetic and Evolutionary Computation Conference, GECCO 2020
Country/TerritoryMexico
CityCancun
Period8/07/2012/07/20

Keywords

  • Comma selection
  • Runtime analysis
  • Theory

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