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Bounds for Multistage Stochastic Programs using Supervised Learning Strategies
Defourny, Boris; Ernst, Damien; Wehenkel, Louis
2009In Watanabe, Osamu; Zeugmann, Thomas (Eds.) Stochastic Algorithms: Foundations and Applications
Peer reviewed
 

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Keywords :
Stochastic Programming; Supervised Learning
Abstract :
[en] We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible decision policy, synthesized by a strategy relying on any scenario tree approximation from stochastic programming and on supervised learning techniques from machine learning.
Disciplines :
Computer science
Author, co-author :
Defourny, Boris ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Dép. d'électric., électron. et informat. (Inst.Montefiore)
Ernst, Damien  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Wehenkel, Louis  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Language :
English
Title :
Bounds for Multistage Stochastic Programs using Supervised Learning Strategies
Publication date :
2009
Event name :
Stochastic Algorithms: Foundations and Applications. Fifth International Symposium, SAGA 2009
Event organizer :
Hokkaido University
Event place :
Sapporo, Japan
Event date :
October 26-28, 2009
Audience :
International
Main work title :
Stochastic Algorithms: Foundations and Applications
Editor :
Watanabe, Osamu
Zeugmann, Thomas
Publisher :
Springer
ISBN/EAN :
9783642049439
Collection name :
Lecture Notes in Computer Sciences; 5792
Pages :
61-73
Peer reviewed :
Peer reviewed
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique
Funding text :
This paper presents research results of the Belgian Network DYSCO (Dynamical Systems, Control, and Optimization), funded by the Interuniversity Attraction Poles Programme, initiated by the Belgian State, Science Policy Office.
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since 08 November 2009

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