A Modified Genetic Algorithm for a Parameter Identification of Fermentation Processes

ABSTRACT

A modified genetic algorithm is proposed for a parameter identification of an E. coli fed-batch fermentation model. In the simple genetic algorithm the best chromosome does not always keep on improving in each generation. Obtained good solutions could be destroyed by either crossover or mutation or both operations. The aim of the modified genetic algorithm is to prevent this disadvantage. In view of the fact that there is no general theory about tuning the genetic algorithm parameters, some adjustments of genetic parameters, according to the regarded problem, are done to improve the conventional genetic algorithm. The simulation results illustrate that the use of proposed modified genetic algorithm for a parameter identification of fermentation processes is highly efficient and effective. The functions and parameter adjustments, proposed here, enhance the algorithm performance. Still more, the implementation of the modified genetic algorithm leads to noticeable decreasing of the solution time.