Preliminary Numerical Experiments in Multiobjective Optimization of a Metallurgical Production Process

This paper reports on preliminary numerical experiments in optimizing coolant flows in continuous casting of steel with respect to multiple objectives. For this purpose, Differential Evolution for Multiobjective Optimization (DEMO) coupled with a reliable numerical simulator of the casting process was applied. The algorithm parameters were initially tuned to balance between the quality of the expected results and the computational cost of the optimization process. Afterwards, suitable sets of coolant flow settings were calculated under conflicting requirements for minimum temperature deviations and predefined core length in the caster. In contrast to solutions produced in single-objective optimization, approximation sets of Pareto optimal fronts obtained in multiobjective optimization provide more information to metallurgists and allow for better insight into the casting process.