Averaging principle for stochastic variational inequalities with application to PDEs with nonlinear Neumann conditions

Abstract

Stochastic variational inequalities have been widely used in various areas. In this paper we establish averaging principles for a separated time-scale system of fully coupled stochastic system characterized by stochastic variational inequalities. Under non-Lipschitz continuous conditions, we show that the classical weak convergence result holds for this type of stochastic systems. Strong convergence is also studied for the cases when the diffusion coefficients of the slow motions do not depend on the fast motion components. As an application, we study the homogenization of generalized backward SDEs and semilinear parabolic variational inequalities with nonlinear Neumann boundary conditions.