General over-relaxed proximal point algorithm involving A-maximal relaxed monotone mappings with applications Original Research Article

A general framework for the over-relaxed proximal point algorithm based on the notion of A-maximal relaxed monotonicity is developed, and then the convergence analysis in the context of solving a general class of nonlinear implicit inclusion problems is explored. Furthermore some auxiliary results of interest involving A-maximal relaxed monotone mappings in a Hilbert space setting are included.