Computing optimal operating policies for the food industry

Food processing plants are usually operated in batch or semi-continuous mode. Dynamic optimization techniques can be used to compute optimal operating policies in order to ensure maximum profits and product quality while guaranteeing food safety. However, the nonlinear and highly constrained nature of food processing models can make their dynamic optimization a daunting task. Here, we analyze the performance of several state of the art methods considering two selected case studies: a semi-continuous fermentor and a thermal sterilization unit. We also propose novel sequential re-optimization strategies in order to avoid convergence problems and to improve computational efficiency.