Blast furnace iron-making optimization model is based on material balance and heat balance of the iron-making process. An optimized mathematical mode, whose objective function were the energy consumption and cost, is established using the method of linear programming. Optimization variables and constraints were determined according to the objective function and the characteristics of the blast furnace process. The optimized results were obtained by designing programs with Lingo software, and the multi-objective optimization was obtained by single objective optimization. The superiority of the model was verified by comparing the calculated data with the actual production data. The optimization model, together with the Origin software, was used to analyze the impact of factors such as the coke rate, blast temperature, injection quantity of coke oven gas on energy consumption and cost. At the meantime, some methods to reduce energy consumption were introduced. The results showed that model is optimized to reduce energy consumption by 24.1 kg/t and cost saved selections 42.7 ￥/t compared with the blast furnace production data, according to the standard coal gauge. Hence, there are several measures to reduce energy consumption and cost savings for the blast furnace: to reduce coke rate, improve the coal injection ratio, increase the amount of coke oven gas injection, enrich the oxygen and improve hot blast temperature.