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Properties of the augmented Lagrangian in nonlinear semidefinite optimization

Properties of the augmented Lagrangian in nonlinear semidefinite optimization
Properties of the augmented Lagrangian in nonlinear semidefinite optimization
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 threshold. An error estimate of the solution, depending on the penalty parameter, is also established
semidefinite programming, augmented lagrangian
0022-3239
437-456
Sun, Jie
1a78c5ea-5948-4bee-a6a0-18757dd13010
Zhang, Li-Wei
2dd52415-7f13-4d81-b74c-5832fe0683e9
Wu, Yue
e279101b-b392-45c4-b894-187e2ded6a5c
Sun, Jie
1a78c5ea-5948-4bee-a6a0-18757dd13010
Zhang, Li-Wei
2dd52415-7f13-4d81-b74c-5832fe0683e9
Wu, Yue
e279101b-b392-45c4-b894-187e2ded6a5c

Sun, Jie, Zhang, Li-Wei and Wu, Yue (2006) Properties of the augmented Lagrangian in nonlinear semidefinite optimization. Journal of Optimization Theory and Applications, 129 (3), 437-456. (doi:10.1007/s10957-006-9078-8).

Record type: Article

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 threshold. An error estimate of the solution, depending on the penalty parameter, is also established

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Published date: 2006
Keywords: semidefinite programming, augmented lagrangian
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Identifiers

Local EPrints ID: 35972
URI: http://eprints.soton.ac.uk/id/eprint/35972
DOI: doi:10.1007/s10957-006-9078-8
ISSN: 0022-3239
PURE UUID: 7ea291f4-9841-4c83-887e-ddcb5c342f29
ORCID for Yue Wu: ORCID iD orcid.org/0000-0002-1881-6003

Catalogue record

Date deposited: 30 Jun 2006
Last modified: 16 Mar 2024 03:39

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Contributors

Author: Jie Sun
Author: Li-Wei Zhang
Author: Yue Wu ORCID iD

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