Uncertainty is a very important factor in process operations. In this paper, a systematic framework is developed to address the problem of accounting for uncertainty in the scheduling decision-making process. The objectives are to increase the schedule flexibility prior to its execution and identify the important parameters and their effects into the scheduling performance. Two approaches are proposed: robust optimization and inference-based sensitivity analysis. The proposed formulation incorporates the consideration of solution robustness and model robustness. Examples are presented to illustrate the applicability of the proposed approach in batch plant scheduling.
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Computer Science Applications