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Ermoliev, Y.M., Gaivoronski, A.A., & 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: | 27 Aug 2021 17:11 |
| URI: | https://pure.iiasa.ac.at/2199 |
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