Policy evaluation and optimization for scheduling under uncertainty

The aim of this project is to develop mathematical models and algorithmic methods for scheduling problems under uncertainty and in particular, for identifying critical activities in the schedule, evaluating the performance of given scheduling policies, and finding optimal policies in a parametric setting.