Brasil | Artículos de revistas
dc.creatorGomes, Francisco A.M.
dc.date2007-01-01
dc.date2014-07-18T20:03:54Z
dc.date2015-11-26T11:39:45Z
dc.date2014-07-18T20:03:54Z
dc.date2015-11-26T11:39:45Z
dc.date.accessioned2018-03-28T20:43:09Z
dc.date.available2018-03-28T20:43:09Z
dc.identifierComputational & Applied Mathematics. Sociedade Brasileira de Matemática Aplicada e Computacional, v. 26, n. 3, p. 337-379, 2007.
dc.identifier1807-0302
dc.identifierS1807-03022007000300003
dc.identifier10.1590/S0101-82052007000300003
dc.identifierhttp://dx.doi.org/10.1590/S0101-82052007000300003
dc.identifierhttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022007000300003
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/38624
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/38624
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1234295
dc.descriptionA sequential quadratic programming algorithm for solving nonlinear programming problems is presented. The new feature of the algorithm is related to the definition of the merit function. Instead of using one penalty parameter per iteration and increasing it as the algorithm progresses, we suggest that a new point is to be accepted if it stays sufficiently below the piecewise linear function defined by some previous iterates on the (f,
dc.descriptionC
dc.description2²)-space. Therefore, the penalty parameter is allowed to decrease between successive iterations. Besides, one need not to decide how to update the penalty parameter. This approach resembles the filter method introduced by Fletcher and Leyffer [Math. Program., 91 (2001), pp. 239-269], but it is less tolerant since a merit function is still used. Numerical comparison with standard methods shows that this strategy is promising.
dc.description337
dc.description379
dc.languageen
dc.publisherSociedade Brasileira de Matemática Aplicada e Computacional
dc.relationComputational & Applied Mathematics
dc.rightsaberto
dc.sourceSciELO
dc.subjectsequential quadratic programming
dc.subjectmerit functions
dc.subjectfilter methods
dc.titleA sequential quadratic programming algorithm that combines merit function and filter ideas
dc.typeArtículos de revistas


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