A multivariate destination policy for geometallurgical variables in mineral value chains using coalition-formation clustering

被引:11
|
作者
Del Castillo, Maria Fernanda [1 ]
Dimitrakopoulos, Roussos [1 ]
机构
[1] McGill Univ, Dept Min & Mat Engn, COSMO Stochast Mine Planning Lab, FDA Bldg,3450 Blvd Robert Bourassa, Montreal, PQ H3A 2A7, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Cooperative game theory; Destination policy; Mining optimization; Priority groups; Clustering; CUTOFF GRADE;
D O I
10.1016/j.resourpol.2016.10.003
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Complex polymetallic mining projects with multiple processing streams tend to require tight blending constraints, with different operational and processing targets. These blending requirements are generally not focused solely on metal grade, but rather on a set of geometallurgical variables that affect the performance of the operation and its ability to meet targets and maximize project value. Because of this, a multivariate destination policy is developed here, based on coalition formation clustering (a line of study of cooperative game theory), which avoids the use of cut-off grades and defines where material is sent by accounting for the value and relation of groups of blocks being processed together. This allows improving investment decisions as a result of optimizing project performance, because the variables that affect blending and processing requirements are actively accounted for in the optimization process. A case study on a copper-gold mine with six destinations is presented, where the method proposed shows significant improvements in meeting processing requirements and increases the expected net present value by 5.6% when compared to a traditional method. This shows that complex processing requirements can be accounted for and respected without any loss of project value.
引用
收藏
页码:322 / 332
页数:11
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