Regularized gradient-projection methods for equilibrium and constrained convex minimization problems

In this article, based on Marino and Xu’s method, an iterative method which combines the regularized gradient-projection algorithm (RGPA) and the averaged mappings approach is proposed for finding a common solution of equilibrium and constrained convex minimization problems. Under suitable condition...

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Veröffentlicht in:Journal of inequalities and applications Jg. 2013; H. 1
Hauptverfasser: Tian, Ming, Huang, Li-Hua
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 14.05.2013
Schlagworte:
Analysis
Applications of Mathematics
Mathematics
Mathematics and Statistics
variational inequality
equilibrium
iterative method
constrained convex minimization
fixed point
ISSN:1029-242X, 1029-242X
Online-Zugang:Volltext
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Zusammenfassung:In this article, based on Marino and Xu’s method, an iterative method which combines the regularized gradient-projection algorithm (RGPA) and the averaged mappings approach is proposed for finding a common solution of equilibrium and constrained convex minimization problems. Under suitable conditions, it is proved that the sequences generated by implicit and explicit schemes converge strongly. The results of this paper extend and improve some existing results. MSC: 58E35, 47H09, 65J15.
ISSN:1029-242X
1029-242X
DOI:10.1186/1029-242X-2013-243