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https://hdl.handle.net/1822/19141
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Costa, L. | - |
dc.contributor.author | Oliveira, P. N. | - |
dc.date.accessioned | 2012-05-07T11:20:07Z | - |
dc.date.available | 2012-05-07T11:20:07Z | - |
dc.date.issued | 2004 | - |
dc.identifier.isbn | 1-4020-7653-3 | - |
dc.identifier.issn | 1384-6485 | por |
dc.identifier.uri | https://hdl.handle.net/1822/19141 | - |
dc.description.abstract | Solving multiobjective engineering problems is, in general, a difficult task. In spite of the success of many approaches, elitism has emerged has an effective way of improving the performance of algorithms. In this paper, a new elitist scheme, by which it is possible to control the size of the elite population, as well as the concentration of points in the approximation to the Pareto-optimal set, is introduced. This new scheme is tested on several multiobjective problems and, it proves to lead to a good compromise between computational time and size of the elite population. | eng |
dc.language.iso | eng | por |
dc.publisher | Kluwer | por |
dc.rights | restrictedAccess | por |
dc.subject | Genetic algorithms | eng |
dc.subject | Multiobjective optimization | eng |
dc.subject | Elitism | eng |
dc.title | An elitist genetic algorithm for multiobjective optimization | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
sdum.publicationstatus | published | por |
oaire.citationStartPage | 217 | por |
oaire.citationEndPage | 236 | por |
oaire.citationVolume | 86 | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Applied Optimization | por |
sdum.conferencePublication | METAHEURISTICS: COMPUTER DECISION-MAKING | por |
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c3.pdf Acesso restrito! | 944,24 kB | Adobe PDF | Ver/Abrir |