Scheduling under uncertainty using MILP sensitivity analysis

The aim of this paper is to develop an integrated framework in order to address the issue of uncertainty in short-term scheduling. The idea of inference-based sensitivity analysis for MILP problem is employed within a branch and bound solution framework to determine the importance of different parameters and constraints and to provide a set of alternative schedules for the range of uncertain parameters under consideration. An illustrative example is considered using the proposed approach and the results are compared with parametric programming and robust optimization.