A parallel subgradient projections method for the convex feasibility problem

An iterative method to solve the convex feasibility problem for a finite family of convex sets is presented. The algorithm consists in the application of a generalization of an acceleration procedure introduced by De Pierro, in a parallel version of the Subgradient Projections Method proposed by Censor and Lent. The generated sequence is shown to converge for any starting point. Some numerical results are presented.