On convex vector optimization problems with possibilistic weights

The convex vector optimization problem is characterized by using a parametric scalarization. The weighting norm approach with possibilistic distribution is used for characterizing the efficient points of the problem. The concept of α-possibly optimal solution is specified for the parametric approach with possibility data. A necessary and sufficient condition for such a solution is established. Some stability notions are redefined and analyzed for the possibilistic problem. A numerical example is given for the sake of illustration.