Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30613
Title: CVAR-based formulation and approximation method for stochastic variational inequalities
Authors: Chen, X 
Lin, G
Keywords: Conditional value at risk
Convergence
D-gap function
Monte Carlo sampling approximation
Smoothing approximation
Stochastic variational inequalities
Issue Date: 2011
Source: Numerical algebra, control and optimization, 2011, v. 1, no. 1, p. 35-48 How to cite?
Journal: Numerical Algebra, Control and Optimization 
Abstract: In this paper, we study the stochastic variational inequality problem (SVIP) from a viewpoint of minimization of conditional value-at-risk. We employ the D-gap residual function for VIPs to define a loss function for SVIPs. In order to reduce the risk of high losses in applications of SVIPs, we use the D-gap function and conditional value-at-risk to present a deterministic minimization reformulation for SVIPs. We show that the new reformulation is a convex program under suitable conditions. Furthermore, by using the smoothing techniques and the Monte Carlo methods, we propose a smoothing approximation method for finding a solution of the new reformulation and show that this method is globally convergent with probability one.
URI: http://hdl.handle.net/10397/30613
ISSN: 2155-3289
DOI: 10.3934/naco.2011.1.35
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

10
Last Week
1
Last month
0
Citations as of Jun 19, 2017

Page view(s)

78
Last Week
5
Last month
Checked on Jun 25, 2017

Google ScholarTM

Check

Altmetric



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