
doi: 10.1155/2022/9991466
In this paper, we concern with the split feasibility problem (SFP) whenever the convex sets involved are composed of level sets. By applying Gradient-projection algorithm which is used to solve constrained convex minimization problem of a real valued convex function, we construct two new algorithms for the split feasibility problem and prove that both of them are convergent weakly to a solution of the feasibility problem. In the end, as an application, we obtain a new algorithm for solving the split equality problem.
Convex programming, Iterative procedures involving nonlinear operators, Applications of functional analysis in optimization, convex analysis, mathematical programming, economics, split feasibility problem: weak convergence, QA1-939, gradient-projection algorithm, Mathematics, Set-valued and variational analysis
Convex programming, Iterative procedures involving nonlinear operators, Applications of functional analysis in optimization, convex analysis, mathematical programming, economics, split feasibility problem: weak convergence, QA1-939, gradient-projection algorithm, Mathematics, Set-valued and variational analysis
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