We study a nonconvex mixed variational inequality problem in \(\mathbb {R}^n\) by using monotonic optimization approach. We show that a class of variational inequality problems can be transformed into a monotonic optimization problem and then propose a branch-reduce-and-bound algorithm as a solution approach. The convergence result of the algorithm is established under increasing assumptions on the cost and constraint functions. Applications to two equilibrium models are presented.
