화학공학소재연구정보센터
Industrial & Engineering Chemistry Research, Vol.43, No.19, 6055-6063, 2004
Multiobjective optimization of a semibatch epoxy polymerization process using the elitist genetic algorithm
Multiobjective Pareto optimal solutions for a semibatch isothermal epoxy polymerization process are obtained by adapting the binary-coded nondominated sorting genetic algorithm II (NSGA II). The number-average molecular weight and polydispersity index are taken as two objectives, where the first one is maximized and the second one is minimized. The decision variables are addition profiles of various reagents, e.g., the amount of addition for monomer, sodium hydroxide, and epichlorohydrin at different times, whereas the solution of all species balance equations is treated as a constraint. Because the number-average molecular weight and polydispersity index are sometimes not sufficient to describe the desired species growth, additional objectives such as the maximization of preferential formation of lower oligomers with the minimization of NaOH addition are also studied. For all practical purposes, semibatch-mode operations are preferred even if for the fulfillment of certain objectives batch-mode operations are theoretically competitive. A well-validated model taking care of all physicochemical aspects of a reaction mechanism is a prerequisite for this kind of study. Process simulation and optimization with close proximity to the available experimental conditions is definitely a distinguishable feature of this work that can direct the results toward actual plant realizations.