Self-starting and Globally Convergent Parameters Estimation Method for Aggregation-Breakage Population Balance Model using Genetic Algorithm

摘要

Some of the main challenges to the estimation of parameters for the aggregation-breakagepopulation equation from experimental data include the determination of a good initial point toensure the convergence of the numerical procedure and also ensuring convergence to the globaloptimum not a local minimum. The initial point is usually determined by trial and error. This methodis very time consuming and convergence to the global minimum is not guaranteed. In this write-up, aprocedure is proposed for choosing good initial points for the optimisation using Genetic Algorithmand then employing a gradient searching optimisation method to speed-up convergence to theminimum point. The method is then validated with simulated data with and without artificial randomerrors.