Numerical comparison of Augmented Lagrangian algorithms for nonconvex problems

dc.creatorBirgin, EG
dc.creatorCastillo, RA
dc.creatorMartinez, JM
dc.date2005
dc.dateMAY
dc.date2014-11-13T14:59:07Z
dc.date2015-11-26T18:07:55Z
dc.date2014-11-13T14:59:07Z
dc.date2015-11-26T18:07:55Z
dc.date.accessioned2018-03-29T00:50:02Z
dc.date.available2018-03-29T00:50:02Z
dc.identifierComputational Optimization And Applications. Springer, v. 31, n. 1, n. 31, n. 55, 2005.
dc.identifier0926-6003
dc.identifierWOS:000229218200002
dc.identifier10.1007/s10589-005-1066-7
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/62221
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/62221
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/62221
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1293698
dc.descriptionAugmented Lagrangian algorithms are very popular tools for solving nonlinear programming problems. At each outer iteration of these methods a simpler optimization problem is solved, for which efficient algorithms can be used, especially when the problems are large. The most famous Augmented Lagrangian algorithm for minimization with inequality constraints is known as Powell-Hestenes-Rockafellar (PHR) method. The main drawback of PHR is that the objective function of the subproblems is not twice continuously differentiable. This is the main motivation for the introduction of many alternative Augmented Lagrangian methods. Most of them have interesting interpretations as proximal point methods for solving the dual problem, when the original nonlinear programming problem is convex. In this paper a numerical comparison between many of these methods is performed using all the suitable problems of the CUTE collection.
dc.description31
dc.description1
dc.description31
dc.description55
dc.languageen
dc.publisherSpringer
dc.publisherDordrecht
dc.publisherHolanda
dc.relationComputational Optimization And Applications
dc.relationComput. Optim. Appl.
dc.rightsfechado
dc.rightshttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dc.sourceWeb of Science
dc.subjectnonlinear programming
dc.subjectAugmented Lagrangian methods
dc.subjectinequality constraints
dc.subjectbenchmarking
dc.subjectalgorithms
dc.subjectAdaptive Precision Control
dc.subjectConstrained Optimization
dc.subjectInequality Constraints
dc.subjectEquality Constraints
dc.subjectProgramming Problems
dc.subjectMultiplier Methods
dc.subjectPenalty-functions
dc.subjectSimple Bounds
dc.subjectConvex
dc.titleNumerical comparison of Augmented Lagrangian algorithms for nonconvex problems
dc.typeArtículos de revistas


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