It is well known that the gradient-projection algorithm (GPA) is very useful in solving constrained convex minimization problems. In this paper, we combine a general iterative method with the gradient-projection algorithm to propose a hybrid gradient-projection algorithm and prove that the sequence generated by the hybrid gradient-projection algorithm converges in norm to a minimizer of constrained convex minimization problems which solves a variational inequality.
"A Hybrid Gradient-Projection Algorithm for Averaged Mappings in Hilbert Spaces." J. Appl. Math. 2012 (SI11) 1 - 14, 2012. https://doi.org/10.1155/2012/782960