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.
|Original language||English (US)|
|Number of pages||6|
|Journal||Computer Aided Chemical Engineering|
|State||Published - 2003|
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Computer Science Applications