On unconstrained optimization problems solved using the canonical duality and triality theories. (1st December 2020)
- Record Type:
- Journal Article
- Title:
- On unconstrained optimization problems solved using the canonical duality and triality theories. (1st December 2020)
- Main Title:
- On unconstrained optimization problems solved using the canonical duality and triality theories
- Authors:
- Zălinescu, C.
- Abstract:
- Abstract : DY Gao solely or together with some of his collaborators applied his Canonical duality theory (CDT) for solving a class of unconstrained optimization problems, getting the so-called triality theorems. Unfortunately, the 'double-min duality' from these results published before 2010 revealed to be false, even if in 2003 DY Gao announced that 'certain additional conditions' are needed for getting it. After 2010 DY Gao together with some of his collaborators published several papers in which they added additional conditions for getting 'double-min' and 'double-max' dualities in the triality theorems. The aim of this paper is to treat rigorosly this kind of problems and to discuss several results concerning the 'triality theory' obtained up to now.
- Is Part Of:
- Optimization. Volume 69:Number 12(2020)
- Journal:
- Optimization
- Issue:
- Volume 69:Number 12(2020)
- Issue Display:
- Volume 69, Issue 12 (2020)
- Year:
- 2020
- Volume:
- 69
- Issue:
- 12
- Issue Sort Value:
- 2020-0069-0012-0000
- Page Start:
- 2551
- Page End:
- 2576
- Publication Date:
- 2020-12-01
- Subjects:
- Canonical duality theory -- extended Lagrangian -- dual function
Mathematical optimization -- Periodicals
519.7 - Journal URLs:
- http://www.tandfonline.com/toc/gopt20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/02331934.2019.1672072 ↗
- Languages:
- English
- ISSNs:
- 0233-1934
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6275.100000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22424.xml