A Critical Note on Empirical (Sample Average, Monte Carlo) Approximation of Solutions to Chance Constrained Programs

DOI10.1007/978-3-642-36062-6_3zbMath1267.90086OpenAlexW1453400417MaRDI QIDQ4927261

René Henrion

Publication date: 19 June 2013

Published in: IFIP Advances in Information and Communication Technology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-36062-6_3

zbMATH Keywords

sample sizechance constrained programmingsample average approximationprobabilistic constraintsempirical approximationconvergence of solution sets

Mathematics Subject Classification ID

Stochastic programming (90C15)

Related Items (5)

Solving joint chance constrained problems using regularization and Benders' decomposition ⋮ Optimization under Rare Chance Constraints ⋮ Solving Chance-Constrained Problems via a Smooth Sample-Based Nonlinear Approximation ⋮ Nonanticipative duality, relaxations, and formulations for chance-constrained stochastic programs ⋮ Proximal bundle methods for nonsmooth DC programming

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