A common solution of equilibrium, constrained convex minimization and fixed point problems. (English) Zbl 1482.47133
Summary: In this paper, we propose a new iterative scheme with the help of the gradient-projection algorithm (GPA) for finding a common solution of an equilibrium problem, a constrained convex minimization problem, and a fixed point problem. Then, we prove some strong convergence theorems which improve and extend some recent results. Moreover, we give a numerical result to show the validity of our main theorem.
MSC:
| 47J25 | Iterative procedures involving nonlinear operators |
| 47H09 | Contraction-type mappings, nonexpansive mappings, \(A\)-proper mappings, etc. |
Keywords:
equilibrium problem; constrained convex minimization problem; averaged mapping; iterative method; fixed point; gradient-projection algorithm; strong convergenceReferences:
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