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Self-adaptive combination of global tabu search and local search for nonlinear equations

dc.contributor.authorRamadas, Gisela C. V.
dc.contributor.authorFernandes, Edite M. G. P.
dc.date.accessioned2014-02-25T17:00:07Z
dc.date.available2014-02-25T17:00:07Z
dc.date.issued2012
dc.description.abstractSolving systems of nonlinear equations is a very important task since the problems emerge mostly through the mathematical modelling of real problems that arise naturally in many branches of engineering and in the physical sciences. The problem can be naturally reformulated as a global optimization problem. In this paper, we show that a self-adaptive combination of a metaheuristic with a classical local search method is able to converge to some difficult problems that are not solved by Newton-type methods.por
dc.identifier.doi10.1080/00207160.2012.687727pt_PT
dc.identifier.issn0020-7160
dc.identifier.issn1029-0265
dc.identifier.urihttp://hdl.handle.net/10400.22/4067
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherTaylor & Francispor
dc.relation.ispartofseriesInternational Journal of Computer Mathematics; Vol. 89, Issue 13-14
dc.relation.publisherversionhttp://www.tandfonline.com/doi/abs/10.1080/00207160.2012.687727#.UwyAgM5qyZRpor
dc.subjectNonlinear equationspor
dc.subjectMetaheuristicpor
dc.subjectTabu searchpor
dc.subjectHooke and Jeeves methodpor
dc.titleSelf-adaptive combination of global tabu search and local search for nonlinear equationspor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage1864por
oaire.citation.issueIssue 13-14
oaire.citation.startPage1847por
oaire.citation.titleInternational Journal of Computer Mathematicspor
oaire.citation.volumeVol. 89por
person.familyNameGonçalves Vieira Ramadas
person.givenNameGisela Cristina
person.identifier.ciencia-id1718-5E35-4A69
person.identifier.orcid0000-0003-3883-2964
person.identifier.scopus-author-id54403520900
rcaap.rightsopenAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublication5b7d05da-a26f-4253-b821-a051a98d6aa8
relation.isAuthorOfPublication.latestForDiscovery5b7d05da-a26f-4253-b821-a051a98d6aa8

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