A projection algorithm for general variational inequalities with perturbed constraint sets

We consider the problem of general variational inequalities, GVI, with nonmonotone operator, in a finite dimensional space. We propose a method to solve GVI that at each iteration considers only one projection on an easy approximation of the constraint set, which is important from a practical point of view. We analyse the convergence of the algorithm under a weak cocoercivity condition, using variational metric analysis. Computational experience is reported and comparative analysis with other two algorithms is also given for the monotone case.