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

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/2843 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/2843 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/2843 archive 351 disk0/00/00/27/89 2016-01-15 01:56:52 2021-08-27 17:12:37 2016-01-15 01:56:52 monograph show 2 Gaivoronski A.A. 1003 Computing Bounds for the Solution of the Stochastic Optimization Problem with Incomplete Information on Distribution of Random Parameters pub iis_met prog_ado 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. 1986-11 published WP-86-072 WP-86-072 10 1273 public working_paper IIASA, Laxenburg, Austria 35 FALSE info:eu-repo/semantics/book