Control vector optimization and genetic algorithms for mixed-integer dynamic optimization in the synthesis of rice drying processes

Clearly such a formidable problem is not easy to solve. Hence, we propose an approach that makes use of two algorithms: a genetic algorithm to search for the best configuration of units and a control vector parameterization approach that optimizes the operating conditions for each configuration. We demonstrate the effectiveness of the approach on a case study.