4.2 Article

Hybrid Proximal-Type and Hybrid Shrinking Projection Algorithms for Equilibrium Problems, Maximal Monotone Operators, and Relatively Nonexpansive Mappings

Journal

NUMERICAL FUNCTIONAL ANALYSIS AND OPTIMIZATION
Volume 31, Issue 7, Pages 763-797

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/01630563.2010.496697

Keywords

Equilibrium problems; Generalized projection; Hybrid proximal-type algorithms; Hybrid shrinking projection algorithms; Maximal monotone operators; Relatively nonexpansive mappings; Strong convergence; Uniformly smooth and uniformly convex Banach spaces

Funding

  1. Shanghai Normal University [DZL707]
  2. Shanghai Municipal Education Commission [09ZZ133]
  3. National Science Foundation of China [10771141]
  4. Ministry of Education of China [20070270004]
  5. Science and Technology Commission of Shanghai Municipality [075105118]
  6. Shanghai Leading Academic Discipline Project [S30405]
  7. National Science Council of Taiwan [NSC 98-2923-E-110-003-MY3]

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In this article, we introduce two hybrid proximal-type algorithms and two hybrid shrinking projection algorithms by using the hybrid proximal-type method and the hybrid shrinking projection method, respectively, for finding a common element of the set of solutions of an equilibrium problem, the set of fixed points of a relatively nonexpansive mapping, and the set of solutions to the equation 0 is an element of Tx for a maximal monotone operator T defined on a uniformly smooth and uniformly convex Banach space. The strong convergence of the sequences generated by the proposed algorithms is established. Our results improve and generalize several known results in the literature.

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