Mixed Integer Linear Programming Model for Optimization of Scrap Mixing and Allocation in a Steel Industry

Steel production using scrap in steel mills is a complex task, impacted by operational constraints, metallurgical requirements, and variable costs. This work proposes a mixed integer linear programming model to support the decision of mixing and metal loading with scrap in the steel mill of a steel mill, considering the concept of value in use in steel races. The model optimizes the production costs associated with raw materials, respecting critical operational and metallurgical constraints of the production process. To evaluate the performance of the model, computational tests were carried out with real data, using a commercial solver. The results indicate the model's ability to generate economically advantageous solutions and offering a practical decision support tool for process engineers. The approach also allows the analysis of different scenarios of scrap availability and cost, contributing to the increase in flexibility and efficiency of the production process.