Multi-objective Optimization of Fed-Batch Bioreactor Towards Lysine Production
The optimal control of fed batch bioreactor is one of the real-world problems that involve simultaneous optimization of several conflicting performance measures. Multi-objective optimization using evolutionary algorithms (EAs) is capable of solving such problems due to the population based stochastic features. These features enable the evolutionary algorithms in generating a set of non-dominated solutions called the Pareto optimal front. In this manuscript, multi-objective differential evolution (MODE) algorithms are used to study the optimal control of the fed batch fermentation of Lysine production. The studied MODE algorithms are MODE-III, Harmonic MODE. Well known test problem, KUR problem is also used to test the Pareto optimal front obtained using both the algorithms.