2003 | OriginalPaper | Chapter
A Note on Quantitative Stability and Empirical Estimates in Stochastic Programming
Authors : Vlasta Kaňková, Michal Houda
Published in: Operations Research Proceedings 2002
Publisher: Springer Berlin Heidelberg
Included in: Professional Book Archive
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
The paper deals with a stability of stochastic programming problems considered with respect to a probability measure space. In particular, the paper deals with the stability of the problems in which the operator of mathematical expectation appears in the objective function, constraints set is “deterministic” and the probability measure space is equipped with the Kolmogorov or the Wasserstein metric. The stability results are furthermore employed to statistical estimates in the stochastic programming problems. Some results on a consistence and a rate of convergence are presented.