Studies on generalized kinetic model and Pareto optimization of a product-driven self-cycling bioprocess
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The aim of this study is the optimization of a product-driven self-cycling bioprocess and presentation of a way to determine the best possible decision variables out of a set of alternatives based on the designed model. Initially, a product-driven generalized kinetic model, which allows a flexible choice of the most appropriate kinetics is designed and analysed. The optimization problem is given as the bi-objective one, where maximization of biomass productivity and minimization of unproductive loss of substrate are the objective functions. Then, the Pareto fronts are calculated for exemplary kinetics. It is found that in the designed bioprocess, a decrease of emptying/refilling fraction and an increase of substrate feeding concentration cause an increase of the biomass productivity. An increase of emptying/refilling fraction and a decrease of substrate feeding concentration cause a decrease of unproductive loss of substrate. The preferred solutions are calculated using the minimum distance from an ideal solution method, while giving proposals of their modifications derived from a decision maker’s reactions to the generated solutions.
KeywordsGeneralized kinetic model Optimization Pareto front Preferred solution Self-cycling bioprocess
Kaibiao Sun would like to thank the China Scholarship Council and Dalian University of Technology for financial support during the period of his overseas study, and to express his gratitude to the Department of Mathematics and Statistics, Memorial University of Newfoundland for its kind hospitality. This work was supported in part by the National Natural Science Foundation of China (No. 11101066) and the Fundamental Research Funds for the Central Universities (No. DUT13LK32).
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