Application of genetic algorithms and simulations for the optimization of batch fermentation control

Batch fermentations are dynamic processes that must be guided along convenient paths to obtain the desired results. Our research deals with the application of computers for advanced control of such processes. We selected beer fermentation, and started to investigate whether it is possible to optimize the process, taking as reference to be improved a real industrial fermentation. A good mathematical model is needed for that, and, as we refer to realistic industrial conditions, we had to develop a new one. Then we started optimization studies, exploring the adaptation of genetic algorithms for our problem. Good results are obtained, furnishing a promising ground for additional improvements. In this paper we describe the process, the new model, the optimization problem, and the solution by genetic algorithms