Cuckoo Search Algorithm for Model Parameter Identification

In this paper, the metaheuristics algorithm Cuckoo Search (CS), is adapted and applied for a model parameter identification of an E. coli fed-batch cultivation process. The dynamics of bacteria growth and substrate (glucose) utilization is described by a system of ordinary nonlinear differential equations. Using real experimental data set from an E. coli MC4110 fed-batch cultivation process a parameter optimization is performed. The simulation results indicate that the applied algorithm is effective and efficient. As a result, a model with high degree of accuracy is obtained applying the CS. The simulation results and comparison with genetic algorithm and ant colony optimization algorithm confirm the effectiveness of the applied CS algorithm in solving a cultivation model parameter identification problem.