Approximations of Evolutionary Inequality with Lipschitz-continuous Functional and Minimally Regular Input Data

Abstract

The convergence and accuracy of approximations of evolutionary inequality with a linear bounded operator and a convex and Lipschitz-continuous functional are investigated. Four types of approximations are considered: the regularization method, the Galerkin semi-discrete scheme, the Rothe scheme and the fully discrete scheme. Approximations are thoroughly studied under sufficiently weak assumptions about the smoothness of the input data. As an example of applying general theoretical results, we study the finite element approximation of second order parabolic variational inequality.