Journal of Applied Mathematics

  • J. Appl. Math.
  • Volume 2012, Special Issue (2012), Article ID 782960, 14 pages.

A Hybrid Gradient-Projection Algorithm for Averaged Mappings in Hilbert Spaces

Ming Tian and Min-Min Li

Full-text: Open access

Abstract

It is well known that the gradient-projection algorithm (GPA) is very useful in solving constrained convex minimization problems. In this paper, we combine a general iterative method with the gradient-projection algorithm to propose a hybrid gradient-projection algorithm and prove that the sequence generated by the hybrid gradient-projection algorithm converges in norm to a minimizer of constrained convex minimization problems which solves a variational inequality.

Article information

Source
J. Appl. Math., Volume 2012, Special Issue (2012), Article ID 782960, 14 pages.

Dates
First available in Project Euclid: 3 January 2013

Permanent link to this document
https://projecteuclid.org/euclid.jam/1357179986

Digital Object Identifier
doi:10.1155/2012/782960

Mathematical Reviews number (MathSciNet)
MR2956504

Zentralblatt MATH identifier
1252.49013

Citation

Tian, Ming; Li, Min-Min. A Hybrid Gradient-Projection Algorithm for Averaged Mappings in Hilbert Spaces. J. Appl. Math. 2012, Special Issue (2012), Article ID 782960, 14 pages. doi:10.1155/2012/782960. https://projecteuclid.org/euclid.jam/1357179986


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