Gradient Projection Algorithm for Strongly Convex Set

In our work we will discuss standard gradient projection algorithm, where a set is strongly convex of radius $R$ and a function is convex, differentiable and its gradient satisfies Lipschitz condition. We proved that under some natural additional conditions algorithm converges with the rate of a geometric progression.