Smoothing and SAA method for stochastic programming problems with non-smooth objective and constraints

被引:0
|
作者
Gui-Hua Lin
Mei-Ju Luo
Jin Zhang
机构
[1] Shanghai University,School of Management
[2] Liaoning University,School of Mathematics
[3] Hong Kong Baptist University,Department of Mathematics
来源
Journal of Global Optimization | 2016年 / 66卷
关键词
Non-smoothness; Smoothing; Sample average approximation; Stochastic mathematical program with equilibrium constraints; 90C15; 90C30; 90C33; 65K05;
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学科分类号
摘要
We consider a stochastic non-smooth programming problem with equality, inequality and abstract constraints, which is a generalization of the problem studied by Xu and Zhang (Math Program 119:371–401, 2009) where only an abstract constraint is considered. We employ a smoothing technique to deal with the non-smoothness and use the sample average approximation techniques to cope with the mathematical expectations. Then, we investigate the convergence properties of the approximation problems. We further apply the approach to solve the stochastic mathematical programs with equilibrium constraints. In addition, we give an illustrative example in economics to show the applicability of proposed approach.
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页码:487 / 510
页数:23
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