Stochastic Optimization Problems with Incomplete Information on Distribution Functions

Ermoliev YM, Gaivoronski AA, & Nedeva C (1983). Stochastic Optimization Problems with Incomplete Information on Distribution Functions. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-83-113

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Abstract

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.

Item Type: Monograph (IIASA Working Paper)
Research Programs: System and Decision Sciences - Core (SDS)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 01:52
Last Modified: 04 Nov 2016 03:21
URI: http://pure.iiasa.ac.at/2199

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