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http://www.repositorio.ufop.br/jspui/handle/123456789/7290
Título: | Memetic self-adaptive evolution strategies applied to the maximum diversity problem. |
Autor(es): | Freitas, Alan Robert Resende de Guimarães, Frederico Gadelha Silva, Rodrigo César Pedrosa Souza, Marcone Jamilson Freitas |
Palavras-chave: | Metaheuristics Evolutionary algorithms |
Data do documento: | 2014 |
Referência: | FREITAS, A. R. R. de et al. Memetic self-adaptive evolution strategies applied to the maximum diversity problem. Optimization Letters, v. 8, n. 2, p. 705-714, fev. 2014. Disponível em: <http://link.springer.com/article/10.1007/s11590-013-0610-0>. Acesso em: 15 fev. 2017. |
Resumo: | The maximum diversity problem consists in finding a subset of elements which have maximum diversity between each other. It is a very important problem due to its general aspect, that implies many practical applications such as facility location, genetics, and product design. We propose a method based on evolution strategies with local search and self-adaptation of the parameters. For all time limits from 1 to 300 s as well as for time to converge to the best solutions known, this method leads to better results when compared to other state-of-the-art algorithms. |
URI: | http://www.repositorio.ufop.br/handle/123456789/7290 |
Link para o artigo: | http://link.springer.com/article/10.1007/s11590-013-0610-0 |
DOI: | https://doi.org/10.1007/s11590-013-0610-0 |
ISSN: | 1862-4480 |
Aparece nas coleções: | DECOM - Artigos publicados em periódicos |
Arquivos associados a este item:
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ARTIGO_MemeticSelfAdaptive.pdf Until 2064-02-15 | 437,03 kB | Adobe PDF | Visualizar/Abrir |
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