Integrated optimization model for alloy addition of basic oxygen furnace based on Particle Swarm Optimization

In the process of BOF(basic oxygen furnace) steelmaking, in order to figure out and optimize the amount of alloy addition during deoxidizing and alloying of tapping, optimization model of this process is very indispensable. For this reason, multi-objective optimization model of alloy addition is developed. Firstly, the prediction model of ladle element content is established with Support Vector Machine. One objective function of multi- objective problem is the error between regulations and the result of the prediction model, the other objective function is the cost of alloy addition. And the alloy addition is optimized with modified dynamic neighborhood multi-objective Particle Swarm Optimization so as to compute the Pareto optimal solution set effectively. The final amount of alloy added is decided according to the practical need.