Alternatives for multiobjective optimization of a polymerization process

The optimal control policies for a polymerization process, particularly for batch free-radical polymerization of methyl methacrylate, were determined using a multiobjective optimization technique. The process objectives considered in the optimization include monomer conversion, polydispersity index, polymerization degree, and total reaction time, weighted and combined in a scalar objective function. The decision variables were the initial concentration of the initiator and the temperature represented by isothermal steps. For solving the optimization problem, several methods based on sequential quadratic programming and a genetic algorithm were used and compared. Combining them into a hybrid method (the genetic algorithm provided the initial values for the traditional iterative method) led to the best results. The aims of this study were to develop an approach for optimizing the polymerization process and to describe alternatives for formulating and solving this problem, emphasizing the importance of user decision in choosing solutions based on technological criteria. (c) 2006 Wiley Periodicals, Inc.