Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10957-006-9078-8
Title: Properties of the augmented Lagrangian in nonlinear semidefinite optimization
Authors: Sun, J. 
Zhang, L.W.
Wu, Y.
Keywords: Augmented Lagrangians
Convergence
Semidefinite programming
Issue Date: 2006
Source: Sun, 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
Abstract: 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. © 2006 Springer Science+Business Media, Inc.
Source Title: Journal of Optimization Theory and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/43962
ISSN: 00223239
DOI: 10.1007/s10957-006-9078-8
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

10
checked on Dec 6, 2017

WEB OF SCIENCETM
Citations

9
checked on Nov 21, 2017

Page view(s)

49
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.