Regularized gradient-projection methods for the constrained convex minimization problem and the zero points of maximal monotone operator

In this paper, based on the viscosity approximation method and the regularized gradient-projection algorithm, we find a common element of the solution set of a constrained convex minimization problem and the set of zero points of the maximal monotone operator problem. In particular, the set of zero...

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Vydáno v:Fixed point theory and applications (Hindawi Publishing Corporation) Ročník 2015; číslo 1; s. 1 - 23
Hlavní autoři: Tian, Ming, Jiao, Si-Wen
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 01.02.2015
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ISSN:1687-1812, 1687-1812
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Abstract In this paper, based on the viscosity approximation method and the regularized gradient-projection algorithm, we find a common element of the solution set of a constrained convex minimization problem and the set of zero points of the maximal monotone operator problem. In particular, the set of zero points of the maximal monotone operator problem can be transformed into the equilibrium problem. Under suitable conditions, new strong convergence theorems are obtained, which are useful in nonlinear analysis and optimization. As an application, we apply our algorithm to solving the split feasibility problem and the constrained convex minimization problem in Hilbert spaces.
AbstractList In this paper, based on the viscosity approximation method and the regularized gradient-projection algorithm, we find a common element of the solution set of a constrained convex minimization problem and the set of zero points of the maximal monotone operator problem. In particular, the set of zero points of the maximal monotone operator problem can be transformed into the equilibrium problem. Under suitable conditions, new strong convergence theorems are obtained, which are useful in nonlinear analysis and optimization. As an application, we apply our algorithm to solving the split feasibility problem and the constrained convex minimization problem in Hilbert spaces.
ArticleNumber 11
Author Tian, Ming
Jiao, Si-Wen
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  surname: Jiao
  fullname: Jiao, Si-Wen
  organization: College of Science, Civil Aviation University of China
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Issue 1
Keywords maximal monotone operator
58E35
fixed point
equilibrium problem
47H09
variational inequality
iterative method
constrained convex minimization
resolvent
65J15
Language English
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Snippet In this paper, based on the viscosity approximation method and the regularized gradient-projection algorithm, we find a common element of the solution set of a...
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SubjectTerms Algorithms
Analysis
Applications of Mathematics
Approximation
Constraints
Convergence
Differential Geometry
Feasibility
Mathematical analysis
Mathematical and Computational Biology
Mathematics
Mathematics and Statistics
Minimization
Operators
Optimization
Topology
Title Regularized gradient-projection methods for the constrained convex minimization problem and the zero points of maximal monotone operator
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