Metallurgy industries often use steel billets, at a proper temperature, to achieve the desired metallurgical, mechanical, and\ndimensional properties of manufactured products. Optimal operation of steel billet reheating furnaces requires the minimization\nof fuel consumption while maintaining a homogeneous material thermal soak. In this study, the operation of a reheating furnace is\nmodeled as a nonlinear optimization problem with the goal of minimizing fuel costwhile satisfying a desired discharge temperature.\nFor this purpose, a genetic algorithms approach is developed. Computational simulation results show that it is possible to minimize\ncosts for different charge temperatures and production rates using the implemented method. Additionally, practical results are\nvalidated with actual data, in a specific scenario, showing a reduction of 3.36% of fuel consumption.
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