- Title
- Abstract convexity for nonconvex optimization duality
- Creator
- Nedic, A.; Ozdaglar, A.; Rubinov, Alex
- Date
- 2007
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/66122
- Identifier
- vital:644
- Identifier
-
https://doi.org/10.1080/02331930701617379
- Identifier
- ISSN:0233-1934
- Abstract
- In this article, we use abstract convexity results to study augmented dual problems for (nonconvex) constrained optimization problems. We consider a nonincreasing function f that is lower semicontinuous at 0 and establish its abstract convexity at 0 with respect to a set of elementary functions defined by nonconvex augmenting functions. We consider three different classes of augmenting functions: nonnegative augmenting functions, bounded-below augmenting functions, and unbounded augmenting functions. We use the abstract convexity results to study augmented optimization duality without imposing boundedness assumptions.; C1
- Publisher
- Taylor and Francis
- Relation
- Optimization Vol. 56, no. 5-6 (2007), p. 655-674
- Rights
- Copyright Taylor and Francis
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0103 Numerical and Computational Mathematics; Abstract convexity; Augmenting functions; Duality; Nonconvex optimisation
- Reviewed
- Hits: 1487
- Visitors: 1396
- Downloads: 0