A new iterative method for generalized equilibrium and constrained convex minimization problems

M. Yazdi

Abstract


The gradient-projection algorithm (GPA) plays an important role in solving constrained convex minimization problems. In this paper, we combine the GPA and averaged mapping approach to propose an explicit composite iterative scheme for finding a common solution of a generalized equilibrium problem and a constrained convex minimization problem. Then, we prove a strong convergence theorem which improves and extends some recent results.

Keywords


Generalized equilibrium problem; constrained convex minimization; averaged mapping; iterative method; variational inequality

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References


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Yazdi, M., New iterative methods for equilibrium and constrained convex minimization problems, Asian-Eur. J. Math. 12 (3) (2019), 12 pp.




DOI: http://dx.doi.org/10.17951/a.2020.74.2.81-99
Date of publication: 2020-12-28 17:42:03
Date of submission: 2020-12-27 17:39:57


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