Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10957-006-9078-8
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dc.titleProperties of the augmented Lagrangian in nonlinear semidefinite optimization
dc.contributor.authorSun, J.
dc.contributor.authorZhang, L.W.
dc.contributor.authorWu, Y.
dc.date.accessioned2013-10-09T03:23:19Z
dc.date.available2013-10-09T03:23:19Z
dc.date.issued2006
dc.identifier.citationSun, J., Zhang, L.W., Wu, Y. (2006). Properties of the augmented Lagrangian in nonlinear semidefinite optimization. Journal of Optimization Theory and Applications 129 (3) : 437-456. ScholarBank@NUS Repository. https://doi.org/10.1007/s10957-006-9078-8
dc.identifier.issn00223239
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/43962
dc.description.abstractWe study the properties of the augmented Lagrangian function for nonlinear semidefinite programming. It is shown that, under a set of sufficient conditions, the augmented Lagrangian algorithm is locally convergent when the penalty parameter is larger than a certain threshold. An error estimate of the solution, depending on the penalty parameter, is also established. © 2006 Springer Science+Business Media, Inc.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s10957-006-9078-8
dc.sourceScopus
dc.subjectAugmented Lagrangians
dc.subjectConvergence
dc.subjectSemidefinite programming
dc.typeArticle
dc.contributor.departmentDECISION SCIENCES
dc.description.doi10.1007/s10957-006-9078-8
dc.description.sourcetitleJournal of Optimization Theory and Applications
dc.description.volume129
dc.description.issue3
dc.description.page437-456
dc.identifier.isiut000242828800006
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