Nonlinear Optimization of Hot Metal Profit in Blast Furnace Based on A Decrease in Coke Consumption Rate Case Study: Esfahan Steel Company

Due to the low quality of domestic coking coal, and increased restrictions on international trade of importing coking coal, iranian steel industry has been encountered serious challenges of supplying coke as the major source of blast furnaces energy while, the vast sources of domestic natural gas and pulverized coal have made it possible to replace coke with these sources of energy in the blast furnaces. high differences in the price of coke with natural gas and pulverized coal, the influence of replacing complexity on the cost of ferrous raw materials, coke, and energy consumption, blast furnace productivity, technical constraints, and carbon dioxide emissions level are the main reasons for conducting this research. in this study, a nonlinear optimization model is developed to determine the profit yield of hot metal in the blast furnace. compared to the available studies, optimal decision making on the supply and replacement of raw materials and energy, together with new constraints, are analyzed. this proposed model was implemented in matlab and validated through the data obtained from esfahan steel company. the results indicate that this model can decrease coke consumption by 26% and is highly effective company benefits.