Surrogate duality for robust optimization
Access this Article
Search this Article
Author(s)
Abstract
Robust optimization problems, which have uncertain data, are considered. We prove surrogate duality theorems for robust quasiconvex optimization problems and surrogate min-max duality theorems for robust convex opti-mization problems. We give necessary and sufficient constraint qualifications for surrogate duality and surrogate min-max duality, and show some exam-ples at which such duality results are used effectively. Moreover, we obtain a surrogate duality theorem and a surrogate min-max duality theorem for semi-definite optimization problems in the face of data uncertainty.
Journal
-
- European Journal of Operational Research
-
European Journal of Operational Research 231(2), 257-262, 2013-12-01