Optimization Under First Order Stochastic Dominance Constraints

Darinka Dentcheva and Andrzej Ruszczynski ()

GE, Growth, Math methods from University Library of Munich, Germany

Abstract: We consider stochastic optimization problems involving stochastic dominance constraints of first order, also called stochastic ordering constraints. They are equivalent to a continuum of probabilistic constraints or chance constraints. We develop first order necessary and sufficient conditions of optimality for these models. We show that the Lagrange multipliers corresponding to stochastic dominance constraints are piecewise constant nondecreasing utility functions. These results extend our theory of stochastic dominance-constrained optimization to the first order case, in which the main challenge is the potential non- convexity of the problem. We also show that the convexification of stochastic ordering relation is equivalent to second order stochastic dominance under rather weak assumptions. This paper appeared as "Semi-Infinite Probabilistic Optimization: First Order Stochastic Dominance Constraints" in "Optimization" 53(2004) 583-- 601.

Keywords: Stochastic dominance; stochastic ordering; stochastic programming; utility functions; semi-infinite optimization; optimality conditions; convexification. (search for similar items in EconPapers)
JEL-codes: C6 D5 D9 (search for similar items in EconPapers)
Date: 2004-03-05, Revised 2005-08-07
New Economics Papers: this item is included in nep-mic
Note: Type of Document - pdf; prepared on WinXP; to print on any;
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (32)

Downloads: (external link)
https://econwpa.ub.uni-muenchen.de/econ-wp/ge/papers/0403/0403002.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpge:0403002

Access Statistics for this paper

More papers in GE, Growth, Math methods from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ( this e-mail address is bad, please contact ).