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Multi-Objective Design Optimization of an Industrial Ldpe Tubular Reactor Using Jumping Gene Adaptations of Nsga and Constraint Handling Principle

Naveen Agrawal1, Gade P. Rangaiah1, Ajay K. Ray2, and Shard K. Gupta3. (1) Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore, 117576, Singapore, (2) Department of Chemical and Biomolecular Engineering, University of Western Ontario, London, ON N6A 5B9, Canada, (3) Department of Chemical Engineering, Indian Institute of Technology Delhi, Delhi, 110 016, India

Multi-objective optimization of an industrial low-density polyethylene (LDPE) tubular reactor is carried out at design stage with the following objectives: maximization of monomer conversion and minimization of normalized side products (methyl, vinyl, and vinylidene groups), both at the reactor end, with end-point constraint on number-average molecular weight (Mn,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 Mn,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 Mn,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.