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dc.contributor.authorGallego, R. A.-
dc.contributor.authorMonticelli, A.-
dc.contributor.authorRomero, R.-
dc.identifier.citationIEEE Transactions on Power Systems. New York: IEEE-Inst Electrical Electronics Engineers Inc., v. 13, n. 3, p. 822-828, 1998.-
dc.description.abstractWe have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)-
dc.sourceWeb of Science-
dc.subjectsimulated annealingpt
dc.subjectgenetic algorithmpt
dc.subjecttabu searchpt
dc.subjectnetwork static expansion planningpt
dc.subjectcombinatorial optimizationpt
dc.titleComparative studies on non-convex optimization methods for transmission network expansion planningen
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationUNICAMP, Campinas, Brazil-
dc.description.affiliationUNESP, FEIS, Ilha Solteira, Brazil-
dc.description.affiliationUnespUNESP, FEIS, Ilha Solteira, Brazil-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofIEEE Transactions on Power Systems-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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