Robust optimization with belief functions

In this paper, an optimization problem with uncertain objective function coefficients is considered. The uncertainty specified by providing a discrete scenario set containing possible realizations of the coefficients. concept belief in traditional and possibilistic setting applied to define admissible probability distributions over set. generalized Hurwicz criterion then used compute solution. complexity resulting explored. Some exact approximation methods solving it are proposed.