Strong convergence with a modified iterative projection method for hierarchical fixed point problems and variational inequalities
Abstract
Let be a nonempty closed convex subset of a real
Hilbert space
. Let
be a sequence of nearly nonexpansive mappings
such that
. Let
be a
-Lipschitzian mapping and
be a
-Lipschitzian and
-strongly monotone operator. This
paper deals with a modified iterative projection method for approximating a
solution of the hierarchical fixed point problem. It is shown that under
certain approximate assumptions on the operators and parameters, the modified
iterative sequence
converges strongly to
which is also the unique solution of the
following variational inequality:
As a special case, this projection method can
be used to find the minimum norm solution of above variational inequality;
namely, the unique solution to the quadratic minimization problem:
. The results here improve and
extend some recent corresponding results of other authors.
Keywords
Kaynakça
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- R. P. Agarwal, D. O’Regan, and D. R. Sahu, Fixed Point Theory for Lipschitzian-Type Mappings with Applications, Topological Fixed Point Theory and Its Applications, Springer, New York, NY, USA, 2009.
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- Y. Yao, R. Chen, Regularized algorithms for hierarchical fixed-point problems, Nonlinear Analysis, 74, 6826–6834, 2011.
- M, Tian and L.H.Huang, Iterativemethods for constrained convexminimization probleminHilbert spaces, Fixed Point Theory and Applications, 2013:105, 2013.
Ayrıntılar
Birincil Dil
İngilizce
Konular
-
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
1 Mart 2016
Gönderilme Tarihi
8 Eylül 2015
Kabul Tarihi
16 Eylül 2015
Yayımlandığı Sayı
Yıl 1970 Cilt: 4 Sayı: 2