Journal article
Strong duality for standard convex programs
Mathematical methods of operations research (Heidelberg, Germany), Vol.94(3), pp.413-436
12/01/2021
DOI: 10.1007/s00186-021-00761-x
Abstract
A primal optimization problem and its dual are in strong duality if either one of the problems has a finite optimal value, then the other one is consistent and has the same optimal value, and the optimal value of the dual problem is attained. In this paper, we study the strong duality without constraint qualifications for a standard convex optimization problem using the bifunction, image space analysis, and polynomial ring approaches. We obtain new strong duals for the primal convex optimization problem, which to the best of our knowledge have not been appeared in the related literature.
Details
- Title: Subtitle
- Strong duality for standard convex programs
- Creators
- Kenneth O. Kortanek - University of PittsburghGuolin Yu - North Minzu UniversityQinghong Zhang - Northern Michigan University
- Resource Type
- Journal article
- Publication Details
- Mathematical methods of operations research (Heidelberg, Germany), Vol.94(3), pp.413-436
- DOI
- 10.1007/s00186-021-00761-x
- ISSN
- 1432-2994
- eISSN
- 1432-5217
- Publisher
- Springer Nature
- Number of pages
- 24
- Grant note
- 11861002 / Natural Science Foundation of China; National Natural Science Foundation of China (NSFC) Nonlinear analysis and financial optimization research center of North Minzu University ZDZX201804 / Key Project of North Minzu University NZ17112 / Natural Science Foundation of Ningxia
- Language
- English
- Date published
- 12/01/2021
- Academic Unit
- Business Analytics
- Record Identifier
- 9984963211602771
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