Interpolating Between Stochastic and Worst-case Optimization

In this talk, I will suggest the study of new models that interpolate between the stringent requirements on distributions for stochastic models and the excessive pessimism of worst-case models for discrete optimization problems. I will make the case for the study, present a few examples and parallel developments and end with a concrete model.