Steady-state selection and efficient covariance matrix update in the multi-objective CMA-ES

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Abstract

The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) combines a mutation operator that adapts its search distribution to the underlying optimization problem with multicriteria selection. Here, a generational and two steady-state selection schemes for the MO-CMA-ES are compared. Further, a recently proposed method for computationally efficient adaptation of the search distribution is evaluated in the context of the MO-CMA-ES.

Original languageEnglish
Title of host publicationEvolutionary Multi-Criterion Optimization - 4th International Conference, EMO 2007, Proceedings
PublisherSpringer Verlag
Pages171-185
Number of pages15
ISBN (Print)9783540709275
DOIs
Publication statusPublished - 1 Jan 2007
Externally publishedYes
Event4th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2007 - Matsushima, Japan
Duration: 5 Mar 20078 Mar 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4403 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2007
Country/TerritoryJapan
CityMatsushima
Period5/03/078/03/07

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