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Mirrored variants of the (1,2)-CMA-ES compared on the noiseless BBOB-2010 testbed

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Abstract

Derandomization by means of mirroring has been recently introduced to enhance the performances of (1, λ)-Evolution-Strategies (ESs) with the aim of designing fast robust local search stochastic algorithms. This paper compares on the BBOB-2010 noiseless benchmark testbed two variants of the (1,2)-CMA-ES where the mirroring method is implemented. Independent restarts are conducted till a total budget of 10 D function evaluations per trial is reached, where D is the dimension of the search space. The results show that the improved variants increase the success probability on 5 (respectively 7) out of 24 test functions in 20D and at the same time are significantly faster on 9 (10) functions in 20D by a factor of about 2-3 (2-4) for a target value of 10-while in no case, the baseline (1,2)-CMA-ES is significantly faster on any tested target function value in 5D and 20D.

Original languageEnglish
Title of host publicationProceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 - Companion Publication
Pages1551-1558
Number of pages8
DOIs
Publication statusPublished - 30 Aug 2010
Externally publishedYes
Event12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010 - Portland, OR, United States
Duration: 7 Jul 201011 Jul 2010

Publication series

NameProceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 - Companion Publication

Conference

Conference12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010
Country/TerritoryUnited States
CityPortland, OR
Period7/07/1011/07/10

Keywords

  • Algorithms

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