Please use this identifier to cite or link to this item: https://doi.org/10.1002/bit.21443
Title: Multi-objective optimization of an industrial penicillin V bioreactor train using non-dominated sorting genetic algorithm
Authors: Fook, C.L.
Rangaiah, G.P. 
Ray, A.K. 
Keywords: Modeling and simulation
Multi-objective optimization
Pareto set
Penicillin bioreactor
Issue Date: 15-Oct-2007
Source: Fook, C.L., Rangaiah, G.P., Ray, A.K. (2007-10-15). Multi-objective optimization of an industrial penicillin V bioreactor train using non-dominated sorting genetic algorithm. Biotechnology and Bioengineering 98 (3) : 586-598. ScholarBank@NUS Repository. https://doi.org/10.1002/bit.21443
Abstract: Bulk of the penicillin produced is used as raw material for semi-synthetic penicillin (such as amoxicillin and ampicillin) and semi-synthetic cephalosporins (such as cephalexin and cefadroxil). In the present paper, an industrial penicillin V bioreactor train is optimized for multiple objectives simultaneously. An industrial train, comprising a bank of identical bioreactors, is run semi-continuously in a synchronous fashion. The fermentation taking place in a bioreactor is modeled using a morphologically structured mechanism. For multi-objective optimization for two and three objectives, the elitist non-dominated sorting genetic algorithm (NSGA-II) is chosen. Instead of a single optimum as in the traditional optimization, a wide range of optimal design and operating conditions depicting trade-offs of key performance indicators such as batch cycle time, yield, profit and penicillin concentration, is successfully obtained. The effects of design and operating variables on the optimal solutions are discussed in detail. © 2007 Wiley Periodicals, Inc.
Source Title: Biotechnology and Bioengineering
URI: http://scholarbank.nus.edu.sg/handle/10635/89530
ISSN: 00063592
DOI: 10.1002/bit.21443
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