Multi-Objective Optimization of Continuous Casting Billet Based on Ant Colony System Algorithm

In continuous casting of steel, a number of parameters have to be set, such as the casting speed and cooling water flowrate, in which the secondary cooling has a considerable influence on cracks and other defects of the billets. The aim of this paper is to develop a optimization algorithm used for solving the optimal secondary cooling water flowrate under different casting speeds with respect to multiple objectives. For this purpose, an optimization algorithm based on multi-objective ant colony system(MOACS) algorithm is developed for solving an optimal control of secondary cooling water distribution according to certain metallurgical criteria and some technological constraints. The optimization method consists of the simulator of continuous casting process, MOACS algorithms linked with two cost function. The use of the developed optimization algorithm for determining optimal setting of cooling parameters demonstrate that better results can be attained in improving the surface temperature distribution.