Wolf-type duality for nonsmooth mathematical programs with equilibrium constraints

Mathematical program with equilibrium constraints is one of the optimization problems whose constraints are used to model certain equilibria in the applications of engineering sciences and economics. Our main aim in the present paper is to investigate the necessary optimality conditions and create a Wolfe type dual problem for such problems. To investigate these conditions, we consider non smooth and non convex optimization problem with equilibrium constraints and suppose that all functions are not necessarily differentiable or convex. For this optimization problem, using the notion of convexificator, which is viewed as a generalization of the idea of subdifferential, we remind some constraint qualifications, stationary conditions, and generalized convexity. Finally, weak duality theorem and strong duality theorem are established under appropriate generalized convexity assumptions and a constraint qualification for an optimization problem with equilibrium constraints based on the notion of convexificators. We also illustrate some of our results by an example.