Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/36834
Título: | Feedback-control operators for improved Pareto-set description: application to a polymer extrusion process |
Autor(es): | Carrano, Eduardo G. Coelho, Dayanne Gouveia Gaspar-Cunha, A. Wanner, Elizabeth F. Takahashi, Ricardo H. C. |
Palavras-chave: | Evolutionary computation Multiobjective optimization Genetic algorithms Polymer extrusion Local search |
Data: | 2015 |
Editora: | Elsevier 1 |
Revista: | Engineering applications of artificial intelligence |
Resumo(s): | 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. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/36834 |
DOI: | 10.1016/j.engappai.2014.10.016 |
ISSN: | 0952-1976 |
Versão da editora: | www.elsevier.com/locate/engappai |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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 |