On the convergence of sample approximations for stochastic programming problems with probabilistic criteria

DOI10.1134/S0005117918020029zbMath1391.90443OpenAlexW2790314402WikidataQ130176238 ScholiaQ130176238MaRDI QIDQ1642031

A. I. Kibzun, Sergey V. Ivanov

Publication date: 20 June 2018

Published in: Automation and Remote Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s0005117918020029

zbMATH Keywords

sample approximationprobabilistic criterionhypoconvergencequantile criterion

Mathematics Subject Classification ID

Stochastic programming (90C15) Dynamic programming (90C39) Optimal stochastic control (93E20)

Related Items (8)

Two-Stage Stochastic Facility Location Model with Quantile Criterion and Choosing Reliability Level ⋮ Application of the Smooth Approximation of the Probability Function in Some Applied Stochastic Programming Problems ⋮ Approximation of probabilistic constraints in stochastic programming problems with a probability measure kernel ⋮ Variable neighborhood search for stochastic linear programming problem with quantile criterion ⋮ Variable neighborhood search for a two-stage stochastic programming problem with a quantile criterion ⋮ General properties of two-stage stochastic programming problems with probabilistic criteria ⋮ A Bilevel Stochastic Programming Problem with Random Parameters in the Follower’s Objective Function ⋮ Sample approximations of bilevel stochastic programming problems with probabilistic and quantile criteria

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