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Stability of epsilon-approximate solutions to convex stochastic programs

Please always quote using this URN:urn:nbn:de:0296-matheon-3324
  • An analysis of convex stochastic programs is provided if the underlying probability distribution is subjected to (small) perturbations. It is shown, in particular, that epsilon-approximate solution sets of convex stochastic programs behave Lipschitz continuous with respect to certain distances of probability distributions that are generated by the relevant integrands. It is shown that these results apply to linear two-stage stochastic programs with random recourse. Consequences are discussed on associating Fortet-Mourier metrics to two-stage models and on the asymptotic behavior of empirical estimates of such models, respectively.

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Metadaten
Author:Werner Römisch, Roger J-B Wets
URN:urn:nbn:de:0296-matheon-3324
Referee:Fredi Tröltzsch
Document Type:Preprint, Research Center Matheon
Language:English
Date of first Publication:2006/04/24
Release Date:2006/04/19
Tag:
Institute:Humboldt-Universität zu Berlin
Weierstraß-Institut für Angewandte Analysis und Stochastik (WIAS)
MSC-Classification:90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C15 Stochastic programming
90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C31 Sensitivity, stability, parametric optimization
Preprint Number:325
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