Two-level primal-dual proximal decomposition technique to solve large scale optimization problems

We describe a primal-dual application of the proximal point algorithm to nonconvex minimization problems. Motivated by the work of Spingarn and more recently by the work of Hamdi et al. about the primal resource-directive decomposition scheme to solve nonlinear separable problems. This paper discusses some local results of a primal-dual regularization approach that leads to a decomposition algorithm.