From black-box complexity to designing new genetic algorithms
Authors:
- Benjamin DoerrBDBenjamin Doerr
- Carola DoerrCDCarola Doerr
- Franziska EbelFEFranziska Ebel
Top Cited Papers
- 1 February 2015
- journal article
- research article
- Published by Elsevier in Theoretical Computer Science
- Vol. 567, 87-104
Abstract
No abstract availableKeywords
Funding Information
- Alexander von Humboldt Foundation
- Agence Nationale de la Recherche (ANR-09-JCJC-0067-01)
This publication has 14 references indexed in Scilit:
- Reducing the arity in unbiased black-box complexityTheoretical Computer Science, 2014
- Tight Bounds on the Optimization Time of a Randomized Search Heuristic on Linear FunctionsCombinatorics, Probability and Computing, 2013
- Ranking-Based Black-Box ComplexityAlgorithmica, 2012
- Black-Box Search by Unbiased VariationAlgorithmica, 2012
- On the Choice of the Parent Population SizeEvolutionary Computation, 2008
- On the Choice of the Offspring Population Size in Evolutionary AlgorithmsEvolutionary Computation, 2005
- On the analysis of the (1+1) evolutionary algorithmTheoretical Computer Science, 2002
- Parameter control in evolutionary algorithmsIEEE Transactions on Evolutionary Computation, 1999
- Toward a Theory of Evolution Strategies: On the Benefits of Sex— the (μ/μ, λ) TheoryEvolutionary Computation, 1995
- Adaptive step size random searchIEEE Transactions on Automatic Control, 1968