Biomimetic adaptations of GA and SA for the robust MO optimization of an industrial nylon-6 reactor

Abstract

A few jumping gene adaptations have been developed for genetic algorithm and simulated annealing. These are inspired by biology and speed up the convergence. These are used to optimize, multiobjectively, an industrial nylon-6 reactor. Nylon-6 is an important commodity plastic, used for fibers, automobile parts, support for electronics materials, gears for toys, etc. The reaction time (increases the profit) and the final concentration of the undesirable cyclic dimer (improves product quality) are minimized. Robust Pareto solutions are obtained in which a ± 1% variation of the decision variables does not lead to significant deviations in the objective functions.