Parameter identification is quite challenging in mixing, which is extensively employed in chemical process industry. Agitated pulp chests are more difficult to characterize because they handle non-Newtonian pulp suspensions and non-ideal flows such as short circuiting, recirculation and channeling. In the present study, we characterize the agitated pulp chests in the continuous time domain, which obviates the restrictions imposed by the discrete time approach. For this purpose, a robust and efficient hybrid genetic algorithm is utilized along with a differential-algebraic model of mixing. Necessary derivatives including auxiliary differential equations are obtained for gradient search. Using realistic large sets of mixing data, both the algorithm and the model are successfully validated before characterizing laboratory-scale agitated pulp chests. Superior characterizations are obtained compared to those yielded by the discrete time domain approach. This outcome highlights the benefit of the continuous time domain approach developed in this work. (C) 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.