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dc.contributor.authorChalco-Cano, Y.-
dc.contributor.authorSilva, G. N.-
dc.contributor.authorRufian-Lizana, A.-
dc.date.accessioned2015-10-21T13:14:46Z-
dc.date.accessioned2016-10-25T21:06:21Z-
dc.date.available2015-10-21T13:14:46Z-
dc.date.available2016-10-25T21:06:21Z-
dc.date.issued2015-08-01-
dc.identifierhttp://www.sciencedirect.com/science/article/pii/S0165011415000640-
dc.identifier.citationFuzzy Sets And Systems. Amsterdam: Elsevier Science Bv, v. 272, p. 60-69, 2015.-
dc.identifier.issn0165-0114-
dc.identifier.urihttp://hdl.handle.net/11449/128869-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/128869-
dc.description.abstractIn this article we consider optimization problems where the objectives are fuzzy functions (fuzzy-valued functions). For this class of fuzzy optimization problems we discuss the Newton method to find a non-dominated solution. For this purpose, we use the generalized Hukuhara differentiability notion, which is the most general concept of existing differentiability for fuzzy functions. This work improves and corrects the Newton method previously proposed in the literature. (C) 2015 Elsevier B.V. All rights reserved.en
dc.description.sponsorshipFONDECYT-Chile-
dc.description.sponsorshipMinisterio de Ciencia y Tecnologia (Spain)-
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
dc.format.extent60-69-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.sourceWeb of Science-
dc.subjectFuzzy optimizationen
dc.subjectGeneralized Hukuhara differentiabilityen
dc.subjectNewton methoden
dc.titleOn the Newton method for solving fuzzy optimization problemsen
dc.typeoutro-
dc.contributor.institutionUniversidad de Tarapacá-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidad de Sevilla-
dc.description.affiliationInstituto de Alta Investigación, Universidad de Tarapacá, Casilla 7D, Arica, Chile-
dc.description.affiliationDepartamento de Estadística e I.O., Universidad de Sevilla, Spain-
dc.description.affiliationUnespInstituto de Biociências, Letras e Ciências Exatas, UNESP – Univ. Estadual Paulista, Câmpus de São José do Rio Preto, Departamento de Matemática Aplicada, São José do Rio Preto, SP, Brazil-
dc.description.sponsorshipIdFONDECYT-Chile: 1120665-
dc.description.sponsorshipIdFONDECYT-Chile: 1120674-
dc.description.sponsorshipIdMinisterio de Ciencia y Tecnologia (Spain): MTM 2010-15383-
dc.description.sponsorshipIdCNPq: 309335/2012-4-
dc.description.sponsorshipIdCNPq: 479109/2013-3-
dc.description.sponsorshipIdFAPESP: 2013/07375-0-
dc.identifier.doihttp://dx.doi.org/10.1016/j.fss.2015.02.001-
dc.identifier.wosWOS:000353512500004-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofFuzzy Sets And Systems-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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