To obtain the benefits of this approach we develop NLP algorithms that are tailored to the structure of DAE optimization problems. In particular, suitable methods are developed with few and many degrees of freedom. Moreover, novel interior point strategies are also included to handle the case of many active constraints. Finally, an overall algorithm is presented that incorporates an adaptive meshing strategy that ensures accurate solutions for both the state and control profiles. All of these concepts are illustrated on a number of dynamic process optimization problems including large scale industrial applications.
Future directions are also explored that deal with larger, more complex models.