On the accurate identification of active constraints

We consider nonlinear programs with inequality constraints, and we focus on the problem of identifying those constraints which will be active at an is olated local solution. The correct identification of active constraints is important from both a theoretical and a practical point of view. Such an id entification removes the combinatorial aspect of the problem and locally re duces the inequality constrained minimization problem to an equality constr ained problem which can be more easily dealt with. We present a new techniq ue which identifies active constraints in a neighborhood of a solution and which requires neither complementary slackness nor uniqueness of the multip liers. We also present extensions to variational inequalities and numerical examples illustrating the identification technique.