Determination of optimised cut-off grade utilising non-linear programming

• Published in: Arabian journal of geosciences Vol. 8; no. 10; pp. 8963 - 8967
• Main Authors: Yasrebi, Amir Bijan, Wetherelt, Andy, Foster, Patrick, Kennedy, Gareth, Kaveh Ahangaran, Dariush, Afzal, Peyman, Asadi, Ahmad
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2015
• Subjects: Earth and Environmental Science; Earth Sciences; Original Paper; Lane algorithm; Profit value (PV); Cut-off grade (COG); Non-linear programming
• ISSN: 1866-7511; 1866-7538
• DOI: 10.1007/s12517-014-1756-5

One of the most fundamental problems in a mining operation is how to recognise an optimum cut-off grade, which defines the grade for discriminating between ore and waste in an ore body, including ore that is extracted at different periods over a mine life period. Therefore, the identification of an optimised cut-off grade (COG) is a crucial function which has to be monitored during the mine life. The main aim of this study is to propose a modified optimum COG model in order to maximise the profit value (PV) for mining projects. Maximising the PV of a mining operation, which is a non-linear programming, is subject to different constraints involving a general grade distribution within a deposit and three stages of production namely mining, concentrating and refining. The proposed computer-based model is more effective in long-term planning of the open pit mines. To provide a better understanding of the algorithm efficiency, a numerical example is given and subsequently solved based on the Lane algorithm. In order to achieve this, the LINGO software was employed.