Journal of Optimization Theory and Applications

, 140:103

Expected Residual Minimization Method for Stochastic Variational Inequality Problems


DOI: 10.1007/s10957-008-9439-6

Cite this article as:
Luo, M.J. & Lin, G.H. J Optim Theory Appl (2009) 140: 103. doi:10.1007/s10957-008-9439-6


This paper considers a stochastic variational inequality problem (SVIP). We first formulate SVIP as an optimization problem (ERM problem) that minimizes the expected residual of the so-called regularized gap function. Then, we focus on a SVIP subclass in which the function involved is assumed to be affine. We study the properties of the ERM problem and propose a quasi-Monte Carlo method for solving the problem. Comprehensive convergence analysis is included as well.


Stochastic variational inequalitiesLevel setsQuasi-Monte Carlo methodsConvergence

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Department of Applied MathematicsDalian University of TechnologyDalianChina