Comparison of the Luus-Jaakola optimization and Gauss-Newton methods for parameter estimation in ordinary differential equation models

The direct search optimization method of Luus and Jaakola (LJ) and the Gauss-Newton (GN) method are employed to solve four parameter optimization problems for chemical and biochemical processes described by ordinary differential equation models. A comparison of the solution methods was thus carried out. It was found that the impact of initial guess values is minimal on the optimal parameters and the optimum. GaussNewton, however, was found to be sensitive to the initial guess. Moreover, GN encountered convergence problems which were alleviated by the use of the Marquardt-Levenberg approach.