MO optimization of phthalic anhydride industrial catalytic reactors using guided GA with the adapted jumping gene operator

Abstract

An industrial phthalic anhydride reactor is simulated using an accurate model incorporating heat transfer with coolant. Two-objective optimization problems for two industrial reactor systems are solved using the elitist non-dominated sorting genetic algorithm with the adapted jumping gene operator, NSGA-II-aJG. Maximization of the yield of phthalic anhydride and minimization of the total length of the catalyst bed are selected as the objective functions. Pareto-optimal solutions are obtained for both the reactor systems studied. An improved algorithm, namely, the guided NSGA-II-aJG, is developed to obtain converged solutions more rapidly for the second reactor system in which the catalyst is distributed over nine zones (to prevent the gas phase temperature from going above the safe limit).