This paper aims at studying, in the image space, an approximation of a vector optimization problem obtained by substituting the involved functions with their G-derivatives. It is shown that, under the hypothesis of G-differentiability, the existence of a semistationary point is equivalent to the...

In this paper we consider a vector optimization problem; we present some scalarization techniques for finding all the vector optimal points of this problem and we discuss the relationships between these methods. Moreover, in the linear case, the study of dual variables is carried on by means of...

The paper deals with vector constrained extremum problems. A separation scheme is recalled; starting from it, a vector Lagrangian duality theory is developed. The linear duality due to Isermann can be embedded in this separation approach. Some classical applications are extended to the...

In this paper we present an application for a multiobjective optimization problem. The objective functions of the primal problem are the risk and the expected pain associated to a portfolio vector. Then, we present a Lagrangian dual problem for it. In order to formulate this problem, we...