Intelligent scheduling in pre-burdening of iron ore: Canopy-Kmeans clustering algorithm and combinatorial optimization
CAO Yue
WANG Ya-lin
HE Hai-ming
YANG Bu-song
GUI Wei-hua
Abstract：This paper presents an intelligent scheduling pre-blending approach based on clustering algorithm and com-binatorial optimization in the burdening process of iron ore. The proposed approach is applied to solve the tough problems which result from the finite chutes, many production constrains, the undeterminable sequence of raw materials and the various raw materials composed of quiet different chemical elements. Firstly, the raw materials are clustered preliminar-ily by Canopy-Kmeans clustering method according to the differences in the content of the SiO2 and TFe respectively. Then, considering all the practical constraints, the chutes scheme of raw materials and the sequence of raw materials are obtained by combinatorial optimization combined with experts'rules and small-scale exhaustive algorithm so that all the raw materials can be scheduled within finite chutes and the chemical elements fluctuations of scheduled blending materials can be as smooth as possible. This pre-burdening approach could benefit in reducing the computing time significantly and reducing the fluctuations of chemical elements, which has been proven by being applied in a practical steel plant in China. Additionally, this approach has appreciable practical significance after compared with original artificial calculation method.
Keywords：pre-burdening of iron orefinite chutesCanopy-Kmeans algorithmcombinatorial optimizationintelligent scheduling
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 947-955 )