SAMPLE AVERAGE APPROXIMATION METHOD FOR SOLVING A DETERMINISTIC FORMULATION FOR BOX CONSTRAINED STOCHASTIC VARIATIONAL INEQUALITY PROBLEMS
DOI10.1142/S0217595912500145zbMath1247.90268OpenAlexW2083533443MaRDI QIDQ2911578
Publication date: 31 August 2012
Published in: Asia-Pacific Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1142/s0217595912500145
convergencelevel setssample average approximationexpected residual minimizationbox constrained stochastic variational inequality
Nonlinear programming (90C30) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)
Cites Work
- Unnamed Item
- Unnamed Item
- Finite-dimensional variational inequality and nonlinear complementarity problems: A survey of theory, algorithms and applications
- Stochastic nonlinear complementarity problem and applications to traffic equilibrium under uncertainty
- Robust solution of monotone stochastic linear complementarity problems
- The \(SC^1\) 1property of an expected residual function arising from stochastic complementarity problems
- Expected residual minimization method for stochastic variational inequality problems
- Equivalent differentiable optimization problems and descent methods for asymmetric variational inequality problems
- Asymptotic properties of statistical estimators in stochastic programming
- Monte Carlo bounding techniques for determinig solution quality in stochastic programs
- A stochastic programming approach for supply chain network design under uncertainty
- The empirical behavior of sampling methods for stochastic programming
- On the Rate of Convergence of Optimal Solutions of Monte Carlo Approximations of Stochastic Programs
- The Sample Average Approximation Method for Stochastic Discrete Optimization
- Stochastic $R_0$ Matrix Linear Complementarity Problems
- A Stochastic Version of a Stackelberg-Nash-Cournot Equilibrium Model
- Engineering and Economic Applications of Complementarity Problems
- A New Unconstrained Differentiable Merit Function for Box Constrained Variational Inequality Problems and a Damped Gauss--Newton Method
- Analysis of Sample-Path Optimization
- Finite-Dimensional Variational Inequalities and Complementarity Problems
- Expected Residual Minimization Method for Stochastic Linear Complementarity Problems
- New restricted NCP functions and their applications to stochastic NCP and stochastic MPEC
- New reformulations for stochastic nonlinear complementarity problems
This page was built for publication: SAMPLE AVERAGE APPROXIMATION METHOD FOR SOLVING A DETERMINISTIC FORMULATION FOR BOX CONSTRAINED STOCHASTIC VARIATIONAL INEQUALITY PROBLEMS