An Asymmetric Proximal Decomposition Method for Convex Programming with Linearly Coupling Constraints
Joint Authors
Wang, Xiangfeng
Fu, Xiaoling
Zhai, Ying
Wang, Haiyan
Source
Advances in Operations Research
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-04-12
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
The problems studied are the separable variational inequalities with linearly coupling constraints.
Some existing decomposition methods are very problem specific, and the computation load is quite costly.
Combining the ideas of proximal point algorithm (PPA) and augmented Lagrangian method (ALM), we propose an asymmetric proximal decomposition method (AsPDM) to solve a wide variety separable problems.
By adding an auxiliary quadratic term to the general Lagrangian function, our method can take advantage of the separable feature.
We also present an inexact version of AsPDM to reduce the computation load of each iteration.
In the computation process, the inexact version only uses the function values.
Moreover, the inexact criterion and the step size can be implemented in parallel.
The convergence of the proposed method is proved, and numerical experiments are employed to show the advantage of AsPDM.
American Psychological Association (APA)
Fu, Xiaoling& Wang, Xiangfeng& Wang, Haiyan& Zhai, Ying. 2012. An Asymmetric Proximal Decomposition Method for Convex Programming with Linearly Coupling Constraints. Advances in Operations Research،Vol. 2012, no. 2012, pp.1-20.
https://search.emarefa.net/detail/BIM-459998
Modern Language Association (MLA)
Fu, Xiaoling…[et al.]. An Asymmetric Proximal Decomposition Method for Convex Programming with Linearly Coupling Constraints. Advances in Operations Research No. 2012 (2012), pp.1-20.
https://search.emarefa.net/detail/BIM-459998
American Medical Association (AMA)
Fu, Xiaoling& Wang, Xiangfeng& Wang, Haiyan& Zhai, Ying. An Asymmetric Proximal Decomposition Method for Convex Programming with Linearly Coupling Constraints. Advances in Operations Research. 2012. Vol. 2012, no. 2012, pp.1-20.
https://search.emarefa.net/detail/BIM-459998
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-459998