On the Analysis of Self-Adaptive Evolutionary Algorithms
dc.contributor.author | Beyer, Hans-Georg | de |
dc.contributor.author | Kalyanmoy Deb | de |
dc.date.accessioned | 2004-12-07T08:20:06Z | |
dc.date.available | 2004-12-07T08:20:06Z | |
dc.date.created | 1999 | de |
dc.date.issued | 2001-10-16 | de |
dc.description.abstract | Due to the exibility in adapting to different fitness landscapes, self-adaptive evolutionary algorithms (SA-EAs) have been gaining popularity in the recent past. In this paper, we postulate the properties that SA-EA operators should have for successful applications. Specifically, population mean and variance of a number of SA-EA operators, such as various real-parameter crossover operators and self-adaptive evolution strategies, are calculated for this purpose. In every case, simulation results are shown to verify the theoretical calculations. The postulations and population variance calculations explain why self-adaptive GAs and ESs have shown similar performance in the past and also suggest appropriate strategy parameter values which must be chosen while applying and comparing different SA-EAs. | en |
dc.format.extent | 436482 bytes | |
dc.format.extent | 485535 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | application/postscript | |
dc.identifier.uri | http://hdl.handle.net/2003/5374 | |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-15381 | |
dc.language.iso | en | de |
dc.publisher | Universität Dortmund | de |
dc.relation.ispartofseries | Reihe Computational Intelligence ; 69 | de |
dc.subject | blend crossover operator | en |
dc.subject | evolution strategies | en |
dc.subject | fuzzy recombination operator | en |
dc.subject | genetic algorithms | en |
dc.subject | population mean | en |
dc.subject | population variance | en |
dc.subject | self-adaptation | en |
dc.subject | simulated binary crossover | en |
dc.subject.ddc | 004 | de |
dc.title | On the Analysis of Self-Adaptive Evolutionary Algorithms | en |
dc.type | Text | de |
dc.type.publicationtype | report | |
dcterms.accessRights | open access |