  In this paper, we study a method for finding robust solutions to
multiobjective optimization problems under uncertainty. We follow the set-based
minmax approach for handling the uncertainties which leads to a certain set
optimization problem with the strict upper type set relation. We introduce,
under some assumptions, a reformulation using instead the strict lower type set
relation without sacrificing the compactness property of the image sets. This
allows to apply vectorization results to characterize the optimal solutions of
these set optimization problems as optimal solutions of a multiobjective
optimization problem. We end up with multiobjective semi-infinite problems
which can then be studied with classical techniques from the literature.
