A class of smoothing SAA methods for a stochastic mathematical program with complementarity constraints

DOI10.1016/j.jmaa.2011.08.073zbMath1228.90070OpenAlexW1996454350MaRDI QIDQ645379

Shuang Lin, Jie Zhang, Li-wei Zhang

Publication date: 15 November 2011

Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/246758

zbMATH Keywords

almost sure convergencesmoothing methodsample average approximationstochastic mathematical program with complementarity constraints

Mathematics Subject Classification ID

Optimality conditions and duality in mathematical programming (90C46) Stochastic programming (90C15) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33) Strong limit theorems (60F15)

Related Items

An implementable SAA nonlinear Lagrange algorithm for constrained minimax stochastic optimization problems ⋮ A sample average approximation regularization method for a stochastic mathematical program with general vertical complementarity constraints ⋮ Convergence analysis of a smoothing SAA method for a stochastic mathematical program with second-order cone complementarity constraints ⋮ Consistency analysis of a local Lipschitz homeomorphism of an SAA normal mapping for a parametric stochastic variational inequality

Uses Software

• SUTIL

Cites Work

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