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

Gui Hua Lin, Mei Ju Luo*, Jin ZHANG

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
1 Downloads (Pure)

Abstract

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.

Original languageEnglish
Pages (from-to)487-510
Number of pages24
JournalJournal of Global Optimization
Volume66
Issue number3
DOIs
Publication statusPublished - 1 Nov 2016

Scopus Subject Areas

  • Computer Science Applications
  • Management Science and Operations Research
  • Control and Optimization
  • Applied Mathematics

User-Defined Keywords

  • Non-smoothness
  • Sample average approximation
  • Smoothing
  • Stochastic mathematical program with equilibrium constraints

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