ORBi: Defourny Boris - Bounds for Multistage Stochastic Programs using Supervised Learning Strategies

Reference : Bounds for Multistage Stochastic Programs using Supervised Learning Strategies


	Document type :	Scientific congresses and symposiums : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/2268/27715

Title :	Bounds for Multistage Stochastic Programs using Supervised Learning Strategies
Language :	English
Author, co-author :	Defourny, Boris [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Dép. d'électric., électron. et informat. (Inst.Montefiore) >]
	Ernst, Damien [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
	Wehenkel, Louis [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Publication date :	2009
Main document title :	Stochastic Algorithms: Foundations and Applications
Editor :	Watanabe, Osamu
	Zeugmann, Thomas
Publisher :	Springer
Collection and collection volume :	Lecture Notes in Computer Sciences; 5792
Pages :	61-73
Peer reviewed :	Yes
On invitation :	No
Audience :	International
ISBN :	9783642049439
Event name :	Stochastic Algorithms: Foundations and Applications. Fifth International Symposium, SAGA 2009
Event date :	October 26-28, 2009
Event organizer :	Hokkaido University
Event place (city) :	Sapporo
Event country :	Japan
Keywords :	[en] 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.
Funders :	Belgian Network DYSCO; FNRS-FRS
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/2268/27715
DOI :	10.1007/978-3-642-04944-6_6
Other URL :	http://www.springerlink.com/content/1700016r11964778
Mentions required by the publisher for OA :	The original publication is available at www.springerlink.com .

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