A study of the continuous casting mold using a pareto-converging genetic algorithm

Abstract

The mold region of the continuous caster, the most widely used casting device used by the steel industry has been modeled through a combination of a steady-state heat transfer approach and a recently developed pareto-converging genetic algorithm (PCGA). Due to highly non-linear nature of the objective functions, as well as the constraints, locating the pareto-front was quite a challenging job in this case. Also, from a physical consideration, the pareto-front needed to be zoomed into the region of equality of two objective functions. PCGA could successfully locate the optima after an extensive search, and the predictions are well in accord with the data provided by a number of industrial casters. © 2001 Published by Elsevier Science Inc. All rights reserved.