Multiobjective Optimization of Process Parameters in Steel Production

The paper presents a multiobjective optimization approach to process parameter optimization in continuous casting of steel, which is the most widely used steel production process. The optimization task is to find parameter values such that the target values of the empirical metallurgical optimization criteria are approached as closely as possible, since this in turn results in high quality of the cast steel. The problem is being solved with a multiobjective evolutionary algorithm coupled with a numerical simulator of the casting process. The resulting trade-o↵ solutions are visualized to support decision-making about the preferred solutions.