Feasible smooth method based on Barzilai---Borwein method for stochastic linear complementarity problem

Authors:
Xiangli Li;Hongwei Liu;Xiaojun Sun
Affiliations:
Department of Applied Mathematics, Xidian University, Xi'an, China;Department of Applied Mathematics, Xidian University, Xi'an, China;Department of Mathematics, Baoji University of Arts and Sciences, Baoji, China
Venue:
Numerical Algorithms
Year:
2011

Citing 9
Cited 0

A nonsmooth inexact Newton method for the solution of large-scale nonlinear complementarity problems

Mathematical Programming: Series A and B - Special issue on computational nonsmooth optimization
Solution of monotone complementarity problems with locally Lipschitzian functions

Mathematical Programming: Series A and B - Special issue on computational nonsmooth optimization
Engineering and Economic Applications of Complementarity Problems

SIAM Review
The Sample Average Approximation Method for Stochastic Discrete Optimization

SIAM Journal on Optimization
Expected Residual Minimization Method for Stochastic Linear Complementarity Problems

Mathematics of Operations Research
Stochastic $R_0$ Matrix Linear Complementarity Problems

SIAM Journal on Optimization
Robust solution of monotone stochastic linear complementarity problems

Mathematical Programming: Series A and B
An affine-scaling interior-point CBB method for box-constrained optimization

Mathematical Programming: Series A and B
Smoothing Projected Gradient Method and Its Application to Stochastic Linear Complementarity Problems

SIAM Journal on Optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a feasible smooth method based on Barzilai---Borwein (BB) for stochastic linear complementarity problem. It is based on the expected residual minimization (ERM) formulation for the stochastic linear complementarity problem. Numerical experiments show that the method is efficient.