Computing Bounds for the Solution of the Stochastic Optimization Problem with Incomplete Information on Distribution of Random Parameters

Gaivoronski AA (1986). Computing Bounds for the Solution of the Stochastic Optimization Problem with Incomplete Information on Distribution of Random Parameters. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-86-072

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Abstract

The paper deals with the solution of a stochastic optimization problem under incomplete information. It is assumed that the distribution of probabilistic parameters is unknown and the only available information comes with observations. In addition the set to which the probabilistic parameters belong is also known. Numerical techniques are proposed which allow to compute upper and lower bounds for the solution of the stochastic optimization problem under these assumptions. These bounds are updated successively after the arrival of new observations.

Item Type: Monograph (IIASA Working Paper)
Research Programs: Adaption and Optimization (ADO)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 01:56
Last Modified: 07 Dec 2016 17:27
URI: http://pure.iiasa.ac.at/2789

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