Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Beyer, Hans-Georg | de |
dc.contributor.author | Deb, Kalyanmoy | de |
dc.date.accessioned | 2004-12-07T08:20:02Z | - |
dc.date.available | 2004-12-07T08:20:02Z | - |
dc.date.created | 1999 | de |
dc.date.issued | 2001-10-16 | de |
dc.identifier.uri | http://hdl.handle.net/2003/5370 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-15294 | - |
dc.description.abstract | Self-adaptation is an essential feature of natural evolution. However, in the context of function optimization, self-adaptation features of evolutionary search algorithms have been explored only with evolution strategy (ES) and evolutionary programming (EP). In this paper, we demonstrate the self-adaptive feature of real-parameter genetic algorithms (GAs) using simulated binary crossover (SBX) operator and without any mutation operator. The connection between the working of self-adaptive ESs and real-parameter GAs with SBX operator is also discussed. Thereafter, the self-adaptive behavior of real-parameter GAs is demonstrated on a number of test problems commonly-used in the ES literature. The remarkable similarity in the working principle of real-parameter GAs and self-adaptive ESs shown in this study suggests the need of emphasizing further studies on self-adaptive GAs. | en |
dc.format.extent | 577230 bytes | - |
dc.format.extent | 907680 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | application/postscript | - |
dc.language.iso | en | de |
dc.publisher | Universität Dortmund | de |
dc.relation.ispartofseries | Reihe Computational Intelligence ; 61 | de |
dc.subject.ddc | 004 | de |
dc.title | Self-Adaptive Genetic Algorithms with Simulated Binary Crossover | en |
dc.type | Text | de |
dc.type.publicationtype | report | - |
dcterms.accessRights | open access | - |
Appears in Collections: | Sonderforschungsbereich (SFB) 531 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
ci61.pdf | DNB | 563.7 kB | Adobe PDF | View/Open |
ci61.ps | 886.41 kB | Postscript | View/Open |
This item is protected by original copyright |
This item is protected by original copyright
rightsstatements.org