Generalized weak sharp minima in cone-constrained convex optimization with applications
In this paper, we consider convex optimization problems with cone constraints (CPC in short). We study generalized weak sharp minima properties for (CPC) in the Banach space and Hilbert space settings, respectively. Some criteria and characterizations for the solution set to be a set of generalized weak sharp minima for (CPC) are derived. As an application, we propose an algorithm for (CPC) in the Hilbert space setting. Convergence analysis of this algorithm is given. Copyright Springer Science+Business Media, LLC 2012
Volume (Year): 53 (2012)
Issue (Month): 3 (December)
|Contact details of provider:|| Web page: http://www.springer.com|
|Order Information:||Web: http://www.springer.com/math/journal/10589|
When requesting a correction, please mention this item's handle: RePEc:spr:coopap:v:53:y:2012:i:3:p:807-821. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.