There are many systems and techniques that address stochastic scheduling problems, based on distinct and sometimes opposite approaches, especially in terms of how scheduling and schedule execution are combined, and if and when knowledge about the uncertainties are taken into account. In many real-life problems, it appears that all these approaches are needed and should be combined, which to our knowledge has never been done. Hence it it first desirable to define a thorough classification of the techniques and systems, exhibiting relevant features: in this paper, we propose a three-dimension typology that distinguishes between proactive, progressive, and revision techniques. Then a theoretical representation model integrating those three distinct approaches is defined. This model serves as a general template within which parameters can be tuned to implement a system that will fit specific application needs: we briefly introduce in this paper our first experimental prototypes which validate our model.