Burden distribution control based on adaptive genetic algorithm in bell-less blast furnace

The proper control of the ratio of ore to coke distribution (ROCD) can achieve energy saving of the blast furnace (BF). In order to achieve the desired ROCD, it is meaningful to search best charging system (especially the burden matrix). This paper deals with the problem of burden distribution control based on the adaptive genetic algorithm and multi-radar data. Firstly, the definition of the ratio of ore to coke (ROC) and the desired ROCD are given. Secondly, according to the desired ROCD, the concrete steps of searching the best burden matrices are presented based on the adaptive genetic algorithm. Then, the operators of the adaptive genetic algorithm (especially the mutation operator) are properly adjusted, according to the actual production process of the bell-less BF. Finally, three computational experiments demonstrate the effectiveness of the method.