Stochastic dynamic optimization of batch and semicontinuous bioprocesses

The dynamic optimization (optimal control) of batch and semicontinuous bioprocesses, like fed-batch fermentation and bioproduct batch separation, has received considerable attention in recent years. These constrained dynamic optimization problems are difficult to solve due to their highly nonlinear character and also due to the fact that they usually are multimodal; therefore most proposed methods may fail to find the global optima. Besides, these methods are not always easy to implement and use, mainly because a laborious preparation and/or transformation of the original problem is needed. Here we present a simple yet powerful method that requires no initial preparation stage and that is useful to solve several complex optimal control problems without convergence difficulties. Two fed-batch bioreactor case studies, taken from the recent literature, and a third case study considering a complex bioproduct dehydration problem are successfully and efficiently solved with our new approach, and its advantages are discussed.