Abstract
The gradient-projection algorithm (GPA) plays an important role in solving constrained convex minimization problems. Based on Tian’s method, we combine GPA and averaged mapping approach to propose implicit and explicit composite iterative algorithms for finding a common solution of an equilibrium and a constrained convex minimization problem for the first time in this paper. Under suitable conditions, strong convergence theorems are obtained.
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