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SPEPS Preprint

Author(s): Steftcho P. Dokov, The University of Texas at Austin
David P. Morton, The University of Texas at Austin
Title: Higher-Order Upper Bounds on the Expectation of a Convex Function
Date of Acceptance: 03.05.2002
Submission Date: 23.01.2002
Series Title: Stochastic Programming E-Print Series
(SPEPS)
Editors: Julie L. Higle; Werner Römisch; Surrajeet Sen
Complete Preprint: pdf (urn:nbn:de:kobv:11-10058406)
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Abstract (eng):
We develop a decreasing sequence of upper bounds on the expectation of a convex function. The n-th term in the sequence uses moments and cross-moments of up to degree n from the underlying random vector. Our work has application to a class of two-stage stochastic programs with recourse. The objective function of such a model can defy computation when: (i) the underlying distribution is assumed to be known only through a limited number of moments or (ii) the function is computationally intractable, even though the distribution is known. A tractable approximating model arises by replacing the objective function by one of our bounding elements. We justify this approach by showing that as n grows, solutions of the order-n approximation solve the true stochastic program.
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Startseite: 12 Zugriffe PDF: 34 Zugriffe Startseite: 4 Zugriffe PDF: 36 Zugriffe PDF: 35 Zugriffe Startseite: 5 Zugriffe PDF: 29 Zugriffe Startseite: 3 Zugriffe PDF: 19 Zugriffe Startseite: 1 Zugriffe PDF: 35 Zugriffe Startseite: 6 Zugriffe PDF: 33 Zugriffe PDF: 22 Zugriffe Startseite: 2 Zugriffe PDF: 27 Zugriffe Startseite: 3 Zugriffe PDF: 33 Zugriffe PDF: 36 Zugriffe Startseite: 1 Zugriffe PDF: 30 Zugriffe Startseite: 3 Zugriffe PDF: 20 Zugriffe Startseite: 4 Zugriffe PDF: 22 Zugriffe Startseite: 3 Zugriffe PDF: 21 Zugriffe Startseite: 1 Zugriffe PDF: 21 Zugriffe Startseite: 3 Zugriffe PDF: 31 Zugriffe
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Startseite 12 4   5 3 1 6   2 3   1 3 4 3 1 3
PDF 34 36 35 29 19 35 33 22 27 33 36 30 20 22 21 21 31

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