Local search with groups of step sizes.

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dc.contributor.authorCosta, Rodolfo Ayala Lopes
dc.contributor.authorFreitas, Alan Robert Resende de
dc.contributor.authorSilva, Rodrigo César Pedrosa
dc.date.accessioned2022-02-07T18:41:55Z
dc.date.available2022-02-07T18:41:55Z
dc.date.issued2021pt_BR
dc.description.abstractLocal search methods for continuous optimization problems tend to be sensitive to the choice of step sizes in their search directions. This paper presents the Local Search with Groups of Step Sizes (LSGSS) method, a derivative-free method that reactively updates groups of promising step sizes for each problem coordinate. The experiments demonstrate LSGSS could find the best solutions for each large-scale benchmark problem when compared to classical methods.pt_BR
dc.identifier.citationCOSTA, R. A. L.; FREITAS, A. R. R. de; SILVA, R. C. P. Local search with groups of step sizes. Operations Research Letters, v. 49, p. 385-392, 2021. Disponível em: <https://www.sciencedirect.com/science/article/abs/pii/S016763772100050X>. Acesso em: 25 ago. 2021.pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.orl.2021.03.009pt_BR
dc.identifier.issn0167-6377
dc.identifier.urihttp://www.repositorio.ufop.br/jspui/handle/123456789/14444
dc.identifier.uri2https://www.sciencedirect.com/science/article/abs/pii/S016763772100050Xpt_BR
dc.language.isoen_USpt_BR
dc.rightsrestritopt_BR
dc.subjectContinuous optimizationpt_BR
dc.subjectDerivative-free local searchpt_BR
dc.titleLocal search with groups of step sizes.pt_BR
dc.typeArtigo publicado em periodicopt_BR
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