Memetic self-adaptive evolution strategies applied to the maximum diversity problem.
| dc.contributor.author | Freitas, Alan Robert Resende de | |
| dc.contributor.author | Guimarães, Frederico Gadelha | |
| dc.contributor.author | Silva, Rodrigo César Pedrosa | |
| dc.contributor.author | Souza, Marcone Jamilson Freitas | |
| dc.date.accessioned | 2017-02-21T16:35:38Z | |
| dc.date.available | 2017-02-21T16:35:38Z | |
| dc.date.issued | 2014 | |
| dc.description.abstract | 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. | pt_BR |
| dc.identifier.citation | 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. | pt_BR |
| dc.identifier.doi | https://doi.org/10.1007/s11590-013-0610-0 | |
| dc.identifier.issn | 1862-4480 | |
| dc.identifier.uri | http://www.repositorio.ufop.br/handle/123456789/7290 | |
| dc.identifier.uri2 | http://link.springer.com/article/10.1007/s11590-013-0610-0 | pt_BR |
| dc.language.iso | en_US | pt_BR |
| dc.rights | restrito | pt_BR |
| dc.subject | Metaheuristics | pt_BR |
| dc.subject | Evolutionary algorithms | pt_BR |
| dc.title | Memetic self-adaptive evolution strategies applied to the maximum diversity problem. | pt_BR |
| dc.type | Artigo publicado em periodico | pt_BR |