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.