ON THE RESOLUTION OF LINEARLY CONSTRAINED CONVEX MINIMIZATION PROBLEMS

dc.creatorFRIEDLANDER, A
dc.creatorMARTINEZ, JM
dc.creatorSANTOS, SA
dc.date1994
dc.dateMAY
dc.date2014-07-30T17:53:10Z
dc.date2015-11-26T17:42:15Z
dc.date2014-07-30T17:53:10Z
dc.date2015-11-26T17:42:15Z
dc.date.accessioned2018-03-29T00:24:05Z
dc.date.available2018-03-29T00:24:05Z
dc.identifierSiam Journal On Optimization. Siam Publications, v. 4, n. 2, n. 331, n. 339, 1994.
dc.identifier1052-6234
dc.identifierWOS:A1994PW28500006
dc.identifier10.1137/0804018
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/68777
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/68777
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1287234
dc.descriptionThe problem of minimizing a twice differentiable convex function f is considered, subject to Ax = b, x greater than or equal to 0, where A is an element of IR(MxN), M, N are large and the feasible region is bounded. It is proven that this problem is equivalent to a ''primal-dual'' box-constrained problem With 2N + M variables. The equivalent problem involves neither penalization parameters nor ad hoc multiplier estimators. This problem is solved using an algorithm for bound constrained minimization that can deal with many variables. Numerical experiments are presented.
dc.description4
dc.description2
dc.description331
dc.description339
dc.languageen
dc.publisherSiam Publications
dc.publisherPhiladelphia
dc.relationSiam Journal On Optimization
dc.relationSIAM J. Optim.
dc.rightsaberto
dc.sourceWeb of Science
dc.subjectLARGE-SCALE LINEARLY CONSTRAINED OPTIMIZATION
dc.subjectBOX-CONSTRAINED PROBLEMS
dc.subjectOPTIMALITY CONDITIONS
dc.subjectSimple Bounds
dc.subjectEm Algorithm
dc.subjectOptimization
dc.subjectConvergence
dc.titleON THE RESOLUTION OF LINEARLY CONSTRAINED CONVEX MINIMIZATION PROBLEMS
dc.typeArtículos de revistas


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