Barycentric Bounds in Stochastic Programming : Theory and Application
Series
International Series in Operations Research and Management Science
ISBN
978-1-4419-1641-9
Type
book section
Date Issued
2011
Author(s)
Editor(s)
Infanger, Gerd
Abstract
The design and analysis of efficient approximation schemes is of fundamental importance in stochastic programming research. Bounding approximations are particularly popular for providing strict error bounds that can be made small by using partitioning techniques. In this article we develop a powerful bounding method for linear multistage stochastic programs with a generalized nonconvex dependence on the random parameters. Thereby, we establish bounds on the recourse functions as well as compact bounding sets for the optimal decisions. We further demonstrate that our bounding methods facilitate the reliable solution of important real-life decision problems. To this end, we solve a stochastic optimization model for the management of non-maturing accounts and compare the bounds on maximum profit obtained with different partitioning strategies.
Language
English
Keywords
stochastic programming
barycentric approximation scheme
bounds
HSG Classification
contribution to scientific community
Refereed
No
Book title
Stochastic programming : the state of the art in honor of George B. Dantzig
Publisher
Springer Science+Business Media, LLC
Publisher place
New York, NY
Number
150
Start page
67
End page
96
Pages
30
Subject(s)
Division(s)
Eprints ID
21872
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Name
Frauendorferetal.pdf
Size
351.18 KB
Format
Adobe PDF
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