A hybrid GA–SQP optimization technique for determination of kinetic parameters of hydrogenation reactions

A hybrid optimization technique, GA–SQP, is developed in which the genetic algorithm (GA) which is a stochastic method is combined with the sequential quadratic programming (SQP) method which is a deterministic method. This method was used to determine the kinetic parameters of the set of highly non...

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Bibliographic Details
Published in:Computers & chemical engineering 2008-07, Vol.32 (7), p.1447-1455
Main Authors: Mansoornejad, Behrang, Mostoufi, Navid, Jalali-Farahani, Farhang
Format: Article
Language:English
Subjects:
Genetic algorithm
Hydrogenation
Kinetic
Optimization
Sequential quadratic programming
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Summary:A hybrid optimization technique, GA–SQP, is developed in which the genetic algorithm (GA) which is a stochastic method is combined with the sequential quadratic programming (SQP) method which is a deterministic method. This method was used to determine the kinetic parameters of the set of highly nonlinear hydrogenation reactions. Catalyst deactivation was also taken into account. The ability of GA and SQP in solving this type of problem was investigated. It was shown that although the SQP is fast, it is not able to solve this problem properly and is very sensitive to the choice of initial point. The GA was able to solve the problem after a large number of generations. It was shown that the new GA–SQP hybrid method is able to determine the final solution considerably faster than the GA while it is not sensitive to the initial point.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2007.06.018