Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.ces.2007.01.030
Title: Design stage optimization of an industrial low-density polyethylene tubular reactor for multiple objectives using NSGA-II and its jumping gene adaptations
Authors: Agrawal, N.
Rangaiah, G.P. 
Ray, A.K.
Gupta, S.K.
Keywords: Constrained-dominance principle
Genetic algorithm
High-pressure polyethylene reactor
Jumping gene
Multi-objective optimization
Issue Date: May-2007
Source: Agrawal, N., Rangaiah, G.P., Ray, A.K., Gupta, S.K. (2007-05). Design stage optimization of an industrial low-density polyethylene tubular reactor for multiple objectives using NSGA-II and its jumping gene adaptations. Chemical Engineering Science 62 (9) : 2346-2365. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ces.2007.01.030
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 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. 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. © 2007 Elsevier Ltd. All rights reserved.
Source Title: Chemical Engineering Science
URI: http://scholarbank.nus.edu.sg/handle/10635/88749
ISSN: 00092509
DOI: 10.1016/j.ces.2007.01.030
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