Abstract Gradient projection methods represent effective tools for solving large-scale constrained optimization problems thanks to their simple implementation and low computational cost per iteration. Despite these good properties, a slow convergence rate can affect gradient schemes, especially when high accurate solutions are needed. A strategy mitigate this drawback consists in properly selec...