Design stage optimization of an industrial low-density polyethylene tubular reactor for multiple objectives using NSGA-II and its jumping gene adaptations

Abstract

Design stage optimization of an industrial low-density polyethylene (LDPE) tubular 
reactor is carried out for two simultaneous objectives: maximization of monomer 
conversion and minimization of normialized side products (methyl, vinyl, and 
vinylidene groups), both at the reactor end, with end-point constraint on number-average 
molecular weight (M-n,M-f) in the product. An inequality constraint is also imposed on 
reactor temperature to avoid run-away condition in the tubular reactor. The binary-coded 
elitist non-dominated sorting genetic algorithm (NSGA-II) and its jumping gene (JG) 
adaptations are used to solve the optimization problem. Both the equality and inequality 
constraints are handled by penalty functions. Only sub-optimal solutions are obtained 
when the equality end-point constraint on M-n,M-f is imposed. But, correct global optimal 
solutions can be assembled from among the Pareto-optimal sets of several problems 
involving a softer constraint on M-n,M-f. A systematic approach of constrained-dominance 
principle for handling constraints is applied for the first time in the binary-coded NSGA-II-aJG 
and NSGA-II-JG, and its performance is compared to the penalty function approach. A 
three-objective optimization problem with the compression power (associated with the 
compression cost) as the third objective along with the aforementioned two objectives, 
is also studied. The results of three-objective optimization are compared with two 
different combinations of two-objective problems. (C) 2007 Elsevier Ltd. All rights 
reserved.