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

Christian Igel*, Thorsten Suttorp, Nikolaus Hansen

*Corresponding author for this work
34 Citations (Scopus)

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, Matsushima, Japan, March 5-8, 2007. Proceedings
EditorsShigeru Obayashi, Kalyanmoy Deb, Carlo Poloni, Tomoyuki Hiroyasu, Tadahiko Murata
Number of pages15
PublisherSpringer
Publication date2007
Pages171-185
ISBN (Print)978-3-540-70927-5
ISBN (Electronic)978-3-540-70928-2
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event4th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2007 - Matsushima, Japan
Duration: 5 Mar 20078 Mar 2007

Conference

Conference4th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2007
Country/TerritoryJapan
CityMatsushima
Period05/03/200708/03/2007
SeriesLecture notes in computer science
Volume4403
ISSN0302-9743

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