Unveiling Optimal Operating Conditions for an Epoxy Polymerization Process Using Multi-objective Evolutionary Computation

The optimization of the epoxy polymerization process involves a number of con icting objectives and more than twenty decision parameters. In this paper, the problem is treated truly as a multiobjective optimization problem and near-Pareto-optimal solutions corresponding to two and three objectives are found using the elitist nondominated sorting GA or NSGA-II. Objectives, such as the number average molecular weight, polydispersity index and reaction time, are considered. The rst two objectives are related to productivity of the polymerization process. The decision variables are discrete addition quantities of various reactants e.g. the amount of addition for bisphenol-A (a monomer), sodium hydroxide and epichlorohydrin at di erent time steps, whereas the satisfaction of all species balance equations is treated as constraints. This study brings out a salient aspect of using an evolutionary approach to multi-objective problem solving. Important and useful patters of addition of reactants are unveiled for di erent optimal trade-o solutions. The systematic approach of multi-stage optimization adopted here for nding optimal operating conditions for epoxy polymerization process should further such studies on other chemical process and real-world optimization problems.