Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/36834
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Campo DC | Valor | Idioma |
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dc.contributor.author | Carrano, Eduardo G. | por |
dc.contributor.author | Coelho, Dayanne Gouveia | por |
dc.contributor.author | Gaspar-Cunha, A. | por |
dc.contributor.author | Wanner, Elizabeth F. | por |
dc.contributor.author | Takahashi, Ricardo H. C. | por |
dc.date.accessioned | 2015-09-03T15:10:08Z | - |
dc.date.available | 2015-09-03T15:10:08Z | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 0952-1976 | por |
dc.identifier.uri | https://hdl.handle.net/1822/36834 | - |
dc.description.abstract | This paper presents a new class of operators for multiobjective evolutionary algorithms that are inspired on feedback-control techniques. The proposed operators, the archive-set reduction and the surface-filling crossover, have the purpose of enhancing the quality of the description of the Pareto-set in multiobjective optimization problems. They act on the Pareto-estimate sample set, performing operations that eliminate archive points in the most crowded regions, and generate new points in the less populated regions, leading to a dynamic equilibrium that tends to generate a uniform sampling of the efficient solution set. The internal parameters of those operators are coordinated by feedback-control inspired techniques, which ensure that the desired equilibrium is attained. Numerical experiments in some benchmark problems and in a real problem of optimization of a single screw extrusion system for polymer processing show that the proposed methodology is able to generate more detailed descriptions of Pareto-optimal fronts than the ones produced by usual algorithms. | por |
dc.description.sponsorship | This work was supported by the Brazilian agencies CNPq, CAPES and FAPEMIG. The authors also acknowledge the support by a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Community Framework Programme. | por |
dc.language.iso | eng | por |
dc.publisher | Elsevier 1 | por |
dc.rights | restrictedAccess | por |
dc.subject | Evolutionary computation | por |
dc.subject | Multiobjective optimization | por |
dc.subject | Genetic algorithms | por |
dc.subject | Polymer extrusion | por |
dc.subject | Local search | por |
dc.title | Feedback-control operators for improved Pareto-set description: application to a polymer extrusion process | por |
dc.type | article | - |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | www.elsevier.com/locate/engappai | por |
sdum.publicationstatus | published | por |
oaire.citationStartPage | 147 | por |
oaire.citationEndPage | 167 | por |
oaire.citationTitle | Engineering applications of artificial intelligence | por |
oaire.citationVolume | 38 | por |
dc.identifier.doi | 10.1016/j.engappai.2014.10.016 | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Engineering applications of artificial intelligence | por |
Aparece nas coleções: | IPC - Artigos em revistas científicas internacionais com arbitragem |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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1-s2.0-S0952197614002565-main.pdf Acesso restrito! | 1,9 MB | Adobe PDF | Ver/Abrir |