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
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Article provided by Springer in its journal Computational Optimization and Applications
Volume (Year): 53 (2012)Handle:
Issue (Month): 3 (December)
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Web page: http://www.springer.com/math/journal/10589
Related researchKeywords: Cone-constrained convex programming
; Generalized weak sharp minima
; Robinson’s constraint qualification
; Systems of differential inclusions
; Tangent cone
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