Estimation of the Necessary Sample Size for Approximation of Stochastic Optimization Problems with Probabilistic Criteria-Reference-Cited by-同舟云学术

Estimation of the Necessary Sample Size for Approximation of Stochastic Optimization Problems with Probabilistic Criteria

Published:2019 Issue: Volume: Page:552-564
ISSN:0302-9743
Container-title:Mathematical Optimization Theory and Operations Research
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Author:

Ivanov Sergey V.^ORCID,Zhenevskaya Irina D.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-22629-9_39

Reference16 articles.

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3. Pagnoncelli, B.K., Ahmed, S., Shapiro, A.: Sample average approximation method for chance constrained programming: theory and applications. J. Optim. Theory Appl. 142, 399–416 (2009). https://doi.org/10.1007/s10957-009-9523-6

4. Kibzun, A.I., Ivanov, S.V.: On the convergence of sample approximations for stochastic programming problems with probabilistic criteria. Automat. Remote Control. 79(2), 216–228 (2018). https://doi.org/10.1134/S0005117918020029

5. Hess, C., Seri, R.: Generic consistency for approximate stochastic programming and statistical problems. SIAM J. Optim. 29(1), 290–317 (2019). https://doi.org/10.1137/17M1156769

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