Multi-objective dynamic optimization of semi-batch polymerization processes

An improved evolutionary algorithm is proposed to perform multi-objective dynamic optimization of a semi-batch styrene polymerization process. The target is to determine the optimal feeding trajectories and the reactor operating temperature, which maximize the monomer conversion rate and minimize the initiator residue concentration in the final product. The optimization problem has been formulated as a multi-objective mixed-integer nonlinear problem (MOMINLP). The proposed approach allows the effective computation of the optimal operating strategies for the production of polymers with the average molecular weight and the polydispersity index required.