Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6108
PIRA download icon_1.1View/Download Full Text
Title: Smoothing projected gradient method and its application to stochastic linear complementarity problems
Authors: Zhang, C
Chen, X 
Issue Date: 2009
Source: SIAM journal on optimization, 2009, v. 20, no. 2, p. 627-649
Abstract: A smoothing projected gradient (SPG) method is proposed for the minimization problem on a closed convex set, where the objective function is locally Lipschitz continuous but nonconvex, nondifferentiable. We show that any accumulation point generated by the SPG method is a stationary point associated with the smoothing function used in the method, which is a Clarke stationary point in many applications. We apply the SPG method to the stochastic linear complementarity problem (SLCP) and image restoration problems. We study the stationary point defined by the directional derivative and provide necessary and sufficient conditions for a local minimizer of the expected residual minimization (ERM) formulation of SLCP. Preliminary numerical experiments using the SPG method for solving randomly generated SLCP and image restoration problems of large sizes show that the SPG method is promising.
Keywords: Smoothing projected gradient method
Nonsmooth
Nonconvex
onstrained optimization
Stochastic linear complementarity problem
Image restoration
Publisher: Society for Industrial and Applied Mathematics
Journal: SIAM journal on optimization 
ISSN: 1052-6234
EISSN: 1095-7189
DOI: 10.1137/070702187
Rights: © 2009 Society for Industrial and Applied Mathematics
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Zhang_Smoothing_Projected_Gradient.pdf551.82 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

107
Last Week
0
Last month
Citations as of Jul 3, 2022

Downloads

241
Citations as of Jul 3, 2022

SCOPUSTM   
Citations

59
Last Week
0
Last month
1
Citations as of Jun 30, 2022

WEB OF SCIENCETM
Citations

57
Last Week
0
Last month
1
Citations as of Jun 30, 2022

Google ScholarTM

Check

Altmetric


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