Modeling of bacterial growth bioprocesses based on heuristic optimization techniques

This paper is concerned with the parameter estimation of a bacterial growth bioprocess using heuristic optimization. The identification algorithms used a dynamic mathematical model containing nine unknown parameters. These parameters were determinate using simulated annealing and genetic algorithms through the minimization of an evaluation function. The reaction kinetics used to simulate microbial growth are the Monod and Haldane equations. The parameter estimation problem is formulated as a multi-modal numerical optimization problem The performances of the two methods are analyzed by numerical simulations.