A Comparison of Variational and Genetic Algorithm Performances in the Optimization of a Polymerization Process

The aim of this work is to compare the performances of two well‐known methods, Minimum Principle and Genetic Algorithm, in the optimization of the methyl methacrylate polymerization process in solution. In order to select a kinetic model for this process, the published kinetic models were reviewed and compared by simulation in similar operating conditions. Based on the kinetic model proposed by Baillagou and Soong (1985), the temperature profile necessary to attain, in a given reaction time, specified values for monomer conversion, number‐average molecular weight and polydispersity index, was calculated. The temperature profiles calculated by the two optimization algorithms are practically identical, but they are obtained with different computational efforts. The results of this comparison are used to draw several conclusions regarding the proficiency of the two methods in the optimization of complex reaction processes. A comparison of the performances of the Minimum Principle and Genetic Algorithm in the optimization of the methyl methacrylate polymerization process in solution is presented. Based on the kinetic model proposed by Baillagou and Soong (1985), the results are used to draw several conclusions regarding the proficiency of the two methods in the optimization of complex reaction processes.