PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Bounds for multistage stochastic programs using supervised learning strategies
Boris Defourny, Damien Ernst and Louis Wehenkel
In: Stochastic Algorithms: Foundations and Applications. Fifth International Symposium, SAGA 2009, Sapporo, Japan(2009).


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.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:6626
Deposited By:Louis Wehenkel
Deposited On:08 March 2010