Strong Duality for General Quadratic Programs with Quadratic Equality Constraints

Duy- Van Nguyen ()
Additional contact information
Duy- Van Nguyen: University of Trier

Journal of Optimization Theory and Applications, 2022, vol. 195, issue 1, No 13, 297-313

Abstract: Abstract In this article, by ‘general quadratic program’ we mean an optimization problem, in which all functions involved are quadratic or linear and local optima can be different from global optima. For a class of general quadratic optimization problems with quadratic equality constraints, the Lagrangian dual problem is constructed, which is a semi-infinite linear program, or equivalently, a copositive program, i.e., a conic program over the closed convex cone of copositive matrices. Solvability of both primal and dual problems and conditions for strong duality are then investigated in connection with some results from nonlinear parametric optimization.

Keywords: Quadratic programming; Strong duality for nonconvex optimization; Copositive matrices; 90C20; 90C26; 90C46 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-022-02082-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:joptap:v:195:y:2022:i:1:d:10.1007_s10957-022-02082-3

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-022-02082-3

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().