Multi-objective optimization of an industrial penicillin V bioreactor train using non-dominated sorting genetic algorithm.
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.
Lee
Fook Choon
FC
Department of Chemical and Biomolecular Engineering, National University of Singapore, Engineering Drive 4, Singapore 117576, Republic of Singapore.
Rangaiah
Gade Pandu
GP
Ray
Ajay Kumar
AK
D000465:Algorithms; D019149:Bioreactors / Q000382:microbiology*; D049109:Cell Proliferation; D002470:Cell Survival; D003198:Computer Simulation; D007218:Industrial Microbiology / Q000379:methods*; D008954:Models, Biological; D010404:Penicillin V / Q000378:metabolism*; D010408:Penicillium chrysogenum / Q000502:physiology*; D011786:Quality Control
D010404:Penicillin V