A GENETIC ALGORITHM-BASED METHOD FOR SOLVING AN INVERSE PROBLEM. APPLICATION TO THE ESTIMATION OF THE PARTICLE SIZE DISTRIBUTION IN COLLOIDAL SYSTEMS.

LUIS A. CLEMENTI; LUIS M. GUGLIOTTA; JORGE R. VEGA

Rosario, Santa Fe

Otro; XIII Reunión de Trabajo en Procesamiento de la Información y Control; 2009

Facultad de Ciencias Exactas, Ingenieria, y Agrimensura. Universidad Nacional de Rosario

Dynamic Light Scattering (DLS) is an optical technique widely used to estimate the particle size distribution (PSD) in colloidal systems. The PSD estimation requires to solve an ill-conditioned inverse problem through some regularization method. In this paper a new method to estimate the PSD of a colloidal system from DLS measurement is proposed. The method utilizes a two-steps optimization algorithm, which is able to estimate an arbitrary-shaped PSD on the basis of the average diameters derived from DLS measurements. In the first step, a genetic algorithm (GA) is used to find the location of the global minimum among several possible local minima. In the second step, a sequential quadratic programming (SQP) method is used to determine the optimum solution by refining the first step estimate. The proposed method was tested with both simulated and experimental examples. Additionally, each PSD was estimated through: i) a GA-based method that assumes a PSD of known shape; and ii) a Tikhonov regularization method. The results showed that the PSD estimated through the GA-based methods are more accurate than those obtained with more standard regularization methods used for solving inverse problems.