Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/7290
Title: Memetic self-adaptive evolution strategies applied to the maximum diversity problem.
Authors: Freitas, Alan Robert Resende de
Guimarães, Frederico Gadelha
Silva, Rodrigo César Pedrosa
Souza, Marcone Jamilson Freitas
Keywords: Metaheuristics
Evolutionary algorithms
Issue Date: 2014
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.
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.
URI: http://www.repositorio.ufop.br/handle/123456789/7290
metadata.dc.identifier.uri2: http://link.springer.com/article/10.1007/s11590-013-0610-0
ISSN: 18624480
Appears in Collections:DECOM - Artigos publicados em periódicos

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