Penalized Sample Average Approximation Methods for Stochastic Mathematical Programs with Complementarity Constraints

DOI10.1287/MOOR.1110.0513zbMath1246.90109OpenAlexW2042028954MaRDI QIDQ2884296

Publication date: 24 May 2012

Published in: Mathematics of Operations Research (Search for Journal in Brave)

Full work available at URL: https://eprints.soton.ac.uk/182207/1/SMPCC-10-Nov-2010.pdf

zbMATH Keywords

MPEC-metric regularity partial exact penalization M-stationary point

Mathematics Subject Classification ID

Sensitivity, stability, parametric optimization (90C31) Stochastic programming (90C15) Set-valued and variational analysis (49J53) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)

Related Items (6)

Stochastic methods based on \(\mathcal{VU}\)-decomposition methods for stochastic convex minimax problems ⋮ Regularizations for stochastic linear variational inequalities ⋮ Quantitative stability analysis of stochastic mathematical programs with vertical complementarity constraints ⋮ Convergence analysis of a smoothing SAA method for a stochastic mathematical program with second-order cone complementarity constraints ⋮ Penalized sample average approximation methods for stochastic programs in economic and secure dispatch of a power system ⋮ STABILITY ANALYSIS OF PARAMETRIC GENERALIZED EQUATIONS AND APPLICATIONS

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