Bibliografie

(eng): Many economic and financial applications lead to determi-nistic optimization problems depending on a probability measure. These problems can be either static (one stage) or dynamic with finite (multistage) or infinite horizon, single-objective or multi-objective. Constraints sets can be either "deterministic", given by probability constraints, or stochastic dominance constraints. We focus on multi-objective problems and second order stochastic dominance constraints. To this end we employ the former results obtained for stochastic (mostly strongly) convex multi-objective problems and results obtained for one-objective problems with second-order stochastic dominance constraints. The relaxation approach will be included in the case of second order stochastic dominance constraints.