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Published in:
2007 | OriginalPaper | Chapter
Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES
Authors : Christian Igel, Thorsten Suttorp, Nikolaus Hansen
Published in: Evolutionary Multi-Criterion Optimization
Publisher: Springer Berlin Heidelberg
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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 multi-criteria 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.