Stochastic Optimization Problems with Incomplete Information on Distribution Functions

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/2204 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/2204 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/2204 archive 351 disk0/00/00/21/99 2016-01-15 01:52:58 2021-08-27 17:11:18 2016-01-15 01:52:58 monograph show 3 Ermoliev Y.M. 1445 Gaivoronski A.A. 1003 Nedeva C. Stochastic Optimization Problems with Incomplete Information on Distribution Functions pub iis_met prog_sds The main purpose of this paper is to discus: numerical optimization procedures, based on duality theory, for problems in which the distribution function is only partially known. The dual problem is formulated as a minimax-type problem in which the "inner" problem of maximization is not concave. Numerical procedures that avoid the difficulties associated with solving the "inner" problem are proposed. 1983-11 published WP-83-113 WP-83-113 338 1273 public working_paper IIASA, Laxenburg, Austria 40 FALSE info:eu-repo/semantics/book