Applied Mathematics and Optimization, Vol.52, No.3, 311-348, 2005
Composition duality methods for mixed variational inclusions
Composition duality methods for mixed variational inclusions are studied in a functional framework of reflexive Banach spaces. On the basis of duality principles, the solvability of maximal monotone and subdifferential mixed variational inclusions is established. For computational purposes, mass-preconditioned augmented formulations are introduced for regularization, as well as three-field and macro-hybrid variational versions. At a finite-dimensional level, corresponding discrete mixed and macro-hybrid internal approximations are discussed, as well as proximal-point iterative algorithms. Primal and dual mixed variational inclusions from contact mechanics illustrate the theory.
Keywords:mixed variational inclusions;duality methods;subdifferential equations;augmented and macro-hybrid formulations;internal approximations;proximal-point algorithms