Modélisation et résolution de problèmes d’optimisation avec un objectif linéaire évidentiel

In this paper, we study a very general class of optimization problems where the objective function is linear and the coefficients are evidential, i.e. where uncertainty is modelled by a belief function. We consider, in this context, two criteria for comparing solutions : maximality and E-admissibility. We provide characterizations for non-dominated solutions with respect to these criteria when the focal sets of the belief function are Cartesian products of compact sets. We show that these characterizations correspond to an established notion in robust optimization.