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论文类型：期刊论文
发表时间：2006-06-01
发表刊物：JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
收录刊物：SCIE、Scopus
卷号：129
期号：3
页面范围：437-456
ISSN号：0022-3239
关键字：semidefinite programming; augmented Lagrangians; convergence
摘要：We 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.