Properties of the Augmented Lagrangian in Nonlinear Semidefinite Optimization

We study the properties of the augmented Lagrangian function for nonlinear semidenite programming. It is shown that, under a set of sufcient conditions, the augmented Lagrangian algorithm is locally convergent when the penalty parameter is larger than a certain threshold. An error estimate of the so...

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Bibliographic Details
Published in:	Journal of optimization theory and applications Vol. 129; no. 3; pp. 437 - 456
Main Authors:	Sun, J., Zhang, L. W., Wu, Y.
Format:	Journal Article
Language:	English
Published:	New York, NY Springer 01.06.2006 Springer Nature B.V
Subjects:	Algorithms Applied sciences Computer programming Eigenvalues Errors Estimates Exact sciences and technology Lagrange multiplier Nonlinearity Operational research and scientific management Operational research. Management science Optimization Programming Quadratic programming Studies Thresholds Semidefinite programming Error estimation convergence Augmented Lagrangian Semi definite programming augmented Lagrangians Non linear programming Lagrangian function
ISSN:	0022-3239, 1573-2878
Online Access:	Get full text
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