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An optimal cut-off grade policy maximises the net present value of an open-pit mining operation and defines a schedule of cut-off grades and the corresponding supply of materials to various destinations. Generally, the cut-off grades are dynamic and decline with the exhaustion of reserves from one year to the next. Thus, stockpiling of the low-grade uneconomic material during earlier years becomes an option to process or blend stockpiled material during later years of mine life. Stockpiling is an established practice in the mining industry and given its significance; as an alternative to traditional cut-off grade models, this article presents a mixed integer programming-based mathematical model that offers an optimal cut-off grade policy with an option to stockpile using three different strategies. The implementation of the new formulation using a case study mining operation available in literature reveals the value of the new model. [ABSTRACT FROM AUTHOR]

Cut-off grade classifies the available supply of ore (valuable) and waste material within a mineralised deposit. Given the mining, processing and refining limitations of a mining operation, an optimal cut-off grade policy ensures that the flow of ore from the mine to the processing and refining facilities is maintained at the maximum possible throughput. This policy defines a schedule of cut-off grades along with corresponding quantities of mineralised material to be mined, processed and metal refined in each period of the scheduling horizon. The criteria that controls the development of cut-off grade policy aligns with the strategic objectives of an operation in order to maximise the discounted value (net present value or NPV) over the life of operation. This paper proposes a new mixed integer linear programming (MILP) based model that maximises NPV subject to the mining, processing, refining capacity constraints and develops an optimal cut-off grade policy for an open pit mining operation with multiple processing streams. An implementation of the proposed method on hypothetical and realistic data promises a relatively higher NPV as compared to the traditional Lane's approach practiced in the mining industry. [ABSTRACT FROM AUTHOR]