Multi-objective optimization of blast furnace dosing and operation based on NSGA-II

Abstract

Blast furnace smelting has high energy consumption and large carbon dioxide emissions, which is an important device for energy saving and carbon reduction transformation in the iron and steel industry. In this paper, a multi-objective optimization model of the blast furnace dosing and operation is proposed. This model is to minimize energy consumption, CO2emissions per tonne of iron and generation cost by adjusting the dosage of different inputs. The Pareto optimal solution set of the model is solved by using the NSGA-II algorithm. To verify the effectiveness of the proposed multi-objective model, the optimized dosing and operation is compared with raw operation data, and the comparison results indicate that the proposed model can significantly improve energy conversion efficiency, reduced the carbon emissions, and save operation costs.