Improved infeasible path optimization for sequential modular simulators—I: The interface

Recently, it was shown that chemical processes modeled by steady-state simulators could be optimized without repeatedly converging the process simulation. Instead, optimization and simulation of the process can be performed simultaneously (along an infeasible path), thus leading to much more efficient performance. In this two-part study, several improvements to this infeasible path approach are described. This first paper deals with improvements to the interface between the optimization algorithm and the process simulator. Here one is primarily concerned with obtaining the necessary function and gradient information for the optimization with minimum computational effort from the process simulator. The architecture of sequential modular simulators, the structure of process optimization problems and any sources of error in obtaining the necessary gradient information for the optimization algorithm are considered. To this end, a chainruling algorithm is derived that allows the incorporation of analytic derivative information for parts of the flowsheet and generally leads to less frequent evaluation of the flowsheet modules. This algorithm is demonstrated on three process optimization problems. The results indicate significant improvement in performance.