Distributionally robust multiobjective optimization with application to risk measure theory

We introduce the concept of a distributionally robust multiobjective optimization problem, which offers a comprehensive framework for addressing issues related to the statistical estimation of unknown probabilities. By employing scalarization methods, we establish optimality conditions, followed by the exploration of applications in financial portfolio management and risk assessment.