Sensitivity analysis and stochastic optimization for open-loop batch operating policy determination

Abstract

The determination of the optimal open-loop operating policy for batch reaction systems under uncertainty is considered. Adjustment of the nominal optimal open-loop operating policy based on worst-case and chance-constrained stochastic optimization approaches are discussed and demonstrated using a commercial pharmaceutical synthesis reaction system. These optimization approaches are compared to a first-order correction based on sensitivity analysis. The results from the study indicate that accounting for parametric uncertainty based on sensitivity analysis provides a poor approximation to stochastic programming.