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Barycentric Scenario Trees in Convex Multistage Stochastic Programming

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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.
   
type journal paper
   
keywords
   
language English
kind of paper journal article
date of appearance 1996
journal Mathematical Programming
publisher Springer-Verlag (Berlin, DE)
ISSN 0025-5610
volume of journal 75
number of issue 2
page(s) 277-294
review not reviewed
   
citation Frauendorfer, K. (1996). Barycentric Scenario Trees in Convex Multistage Stochastic Programming. Mathematical Programming, 75(2), 277-294.