Optimization with a class of multivariate integral stochastic order constraints

We study convex optimization problems with a class of multivariate integral stochastic order constraints defined in terms of parametrized families of increasing concave functions. We show that utility functions act as the Lagrange multipliers of the stochastic order constraints in this general setti...

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Bibliographic Details
Published inAnnals of operations research Vol. 206; no. 1; pp. 147 - 162
Main Authors Haskell, William B., Shanthikumar, J. George, Shen, Z. Max
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.07.2013
Springer
Springer Nature B.V
Subjects
Analysis
Banach spaces
Business and Management
Combinatorics
Integrals
Lagrange multiplier
Lagrange multipliers
Mathematical optimization
Nonlinear programming
Operations research
Operations Research/Decision Theory
Optimization
Random variables
Searching
Stochastic analysis
Stochasticity
Studies
Theory of Computation
Utilities
Utility functions
United States
Stochastic Order
Concave Function
Order Stochastic Dominance
Stochastic Dominance
Slater Condition
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Summary:We study convex optimization problems with a class of multivariate integral stochastic order constraints defined in terms of parametrized families of increasing concave functions. We show that utility functions act as the Lagrange multipliers of the stochastic order constraints in this general setting, and that the dual problem is a search over utility functions. Practical implementation issues are discussed.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-013-1337-0