A new penalization tool in scalar and vector optimizations

In this work we employ a new method to penalize scalar and vector optimization problems by means of a functional known in the literature as the directional minimal time function. We show that this new approach is useful also for the strong Pareto optimality and then we prove, for this kind of solutions, a result concerning necessary optimality conditions expressed in terms of Mordukhovich generalized differentiation.