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Publication details

The Expected Loss in the Discretization of Multistage Stochastic Programming Problems - Estimation and Convergence Rate

Journal Article

Šmíd Martin

serial: Annals of Operations Research vol.165, 1 (2009), p. 29-45

research: CEZ:AV0Z10750506

project(s): GA402/04/1294, GA ČR

keywords: multistage stochastic programming problems, approximation, discretization, Monte Carlo

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abstract (eng):

In the present paper, the approximate computation of a multistage stochastic programming problem (MSSPP) is studied. First, the MSSPP and its discretization are defined. Second, the expected loss caused by the usage of the `approximate'' solution instead of the ``exact'' one is studied. Third, new results concerning approximate computation of expectations are presented. Finally, the main results of the paper - an upper bound of the expected loss and an estimate of the convergence rate of the expected loss - are stated.

abstract (cze):

V článku presentujeme přibližný výpočet vícestupňového problému stochastického programování.


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Last modification: 21.12.2012
Institute of Information Theory and Automation