Purpose
– The purpose of this paper is to provide a decision-making tool on where to send mining parcels extracted in such a way as to minimize losses arising from mis-classification. The problem is complicated because actual values of mining parcels cannot be known and the decision is made on the basis of the estimation/simulations of the parcels generated from sparse data.
Design/methodology/approach
– The loss minimization associated with mis-classification is formulated as a non-linear optimization problem and solved by successive mixed integer programming. By assigning reasonable values to some variables making problem non-linear, the problem is converted to a mixed integer programming (MIP) and is solved by a standard MIP optimization engine.
Findings
– A case study was conducted to see the performance of the proposed approach on a deposit with gold and silver variables. The proposed approach was also compared with conventional grade control approaches. The results showed that the approach proposed could be used for solving grade quality control problem.
Practical implications
– Grade quality control problem is well-known problem and there is no effective solution approach. This paper proposes to solve the problem through standard operation research software. As such, mine planner and engineers have a means to deal with grade quality problem in mining operations.
Originality/value
– The paper formulates multi-variable grade quality control problem as an optimization problem on the contrary to previous one-shot approaches. This can increase profit and operation efficiency. The research also use target grades rather than cut-off grade posing problems in mining operations.