Comparison of optimization algorithms for modeling of Haldane-type growth kinetics during phenol and benzene degradation

In this study, three optimization algorithms (discretized domain, Monte Carlo, steepest descent) were compared to determine the best algorithm for estimation of Haldane-type microbial growth kinetic parameters. Application of these algorithms to growth data measured during phenol and benzene degradation showed different results in the estimated parameters obtained under various boundary conditions and growth phases. Regardless of the specific algorithm used, the factor with the greatest influence on parameter estimation was the boundary condition for the half-saturation constant (K_S), although the parameters were also sensitive to the growth phase for phenol. Among the three algorithms, Monte Carlo was found to be the best and most consistent. The estimated parameters of phenol and benzene using an appropriate boundary value of K_S were comparable with the outputs reported in previous studies, but those derived with inappropriate boundary values were not consistent with previously reported data.