Solution of an inverse adsorption problem with an epidemic genetic algorithm and the generalized extremal optimization algorithm

In the present work two recently developed stochastic methods, the epidemic genetic algorithm and the generalized extremal optimization algorithm are used for the solution of an inverse mass transfer problem, which is implicitly formulated as an optimization problem, for the estimation of parameters associated with the adsorption of biomolecules in resin beds. The estimates obtained with both methods present good accuracy, even in the presence of noisy data, provided that the model and experiment used are sensitive to the parameters being estimated. With Thomas' model for the direct mass transfer problem and real experimental data for lisozyme in adsorption columns, it is possible to estimate the maximum adsorption capacity in Langmuir's adsorption isotherm.