Barycentric Scenario Trees in Convex Multistage Stochastic Programming
Journal
Mathematical Programming
ISSN
0025-5610
Type
journal article
Date Issued
1996
Author(s)
Abstract
This work deals with the approximation of convex stochastic multistage programs allowing prices and demand to be stochastic with compact support. Based on earlier results, sequences of barycentric scenario trees with associated probability trees are derived for minorizing and majorizing the given problem. Error bounds for the optimal policies of the approximate problem and duality analysis with respect to the stochastic data determine the scenarios which improve the approximation. Convergence of the approximate solutions is proven under the stated assumptions. Preliminary computational results are outlined.
Language
English
HSG Classification
not classified
Refereed
No
Publisher
Springer-Verlag
Publisher place
Berlin, DE
Volume
75
Number
2
Start page
277
End page
294
Pages
18
Subject(s)
Division(s)
Eprints ID
7093