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DC Element | Wert | Sprache |
---|---|---|
dc.contributor.author | Horoba, Christian | de |
dc.contributor.author | Neumann, Frank | de |
dc.date.accessioned | 2009-05-12T16:02:21Z | - |
dc.date.available | 2009-05-12T16:02:21Z | - |
dc.date.issued | 2008-12 | de |
dc.identifier.uri | http://hdl.handle.net/2003/26164 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-9019 | - |
dc.description.abstract | Often the Pareto front of a multi-objective optimization problem grows exponentially with the problem size. In this case, it is not possible to compute the whole Pareto front efficiently and one is interested in good approximations. We consider how evolutionary algorithms can achieve such approximations by using different diversity mechanisms. We discuss some well-known approaches such as the density estimator and the e-dominance approach and point out how and when such mechanisms provably help to obtain good additive approximations of the Pareto-optimal set. | en |
dc.language.iso | en | de |
dc.relation.ispartofseries | Reihe CI; 257-08 | de |
dc.subject.ddc | 004 | de |
dc.title | Additive approximations of pareto-optimal sets by evolutionary multi-objective algorithms | en |
dc.type | Text | de |
dc.type.publicationtype | report | de |
dcterms.accessRights | open access | - |
Enthalten in den Sammlungen: | Sonderforschungsbereich (SFB) 531 |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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25708.pdf | DNB | 235.32 kB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource ist urheberrechtlich geschützt. |
Diese Ressource ist urheberrechtlich geschützt.
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