THE OVER-RELAXED η-PROXIMAL POINT ALGORITHM AND NONLINEAR VARIATIONAL INCLUSION PROBLEMS

Abstract

The over-relaxed (\eta)-proximal point algorithm in the context of solving a class of inclusion problems, based on the notion of maximal (\eta)-monotonicity, is developed. Convergence analysis for the over-relaxed (\eta)-proximal point algorithm is examined, and finally, some specializations are included. Furthermore, we remark that the Yosida approximation can be generalized in light of maximal (\eta)-monotonicity, and then it can be applied to first-order evolution equations/inclusions.