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Gürkan, G., Ozge, A.Y. and Robinson, S.M. (1999) Sample-Path Solution of Stochastic Variational Inequalities. Mathematical Programming, 84, 313-333.
http://link.springer.com/article/10.1007/s101070050024
http://dx.doi.org/10.1007/s101070050024

has been cited by the following article:

• TITLE: A New Conjugate Gradient Projection Method for Solving Stochastic Generalized Linear Complementarity Problems

  AUTHORS: Zhimin Liu, Shouqiang Du, Ruiying Wang

  KEYWORDS: Stochastic Generalized Linear Complementarity Problems, Fischer-Burmeister Function, Conjugate Gradient Projection Method, Global Convergence

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.4 No.6, June 13, 2016

  ABSTRACT: In this paper, a class of the stochastic generalized linear complementarity problems with finitely many elements is proposed for the first time. Based on the Fischer-Burmeister function, a new conjugate gradient projection method is given for solving the stochastic generalized linear complementarity problems. The global convergence of the conjugate gradient projection method is proved and the related numerical results are also reported.