A unified approach to uncertain optimization

In this paper we consider uncertain scalar optimization problems with infinite scenario sets. We apply methods from vector optimization in general spaces, set-valued optimization and scalarization techniques to develop a unified characterization of different concepts of robust optimization and stochastic programming. These methods provide new insights on the interrelation between different concepts for handling uncertainties and naturally lead to new concepts of robustness.