Abstract
This paper describes an approach to optimising processing and stockpiling decisions in an open pit mine in order to minimise the deviation from production targets. The solution involves determining decisions on the destination of ore as it is mined: whether to use ore in a product directly as it is extracted from the ground, or to stockpile and use later. Experimental results are provided for a variable threshold based selection heuristic and an approach that applies evolutionary computation to find better solutions.
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Acknowledgement
This work was supported by the Australian Research council through grant DP130104395. Some of the methods used in this paper are based on work done by delegates at the 2016 Mathematics in Industry Study Group workshop, in particular the contributions to developing the simulation and the selection cone heuristic method are gratefully acknowledged.
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Ghandar, A. (2017). Evolutionary Computation to Determine Product Builds in Open Pit Mining. In: Shi, Y., et al. Simulated Evolution and Learning. SEAL 2017. Lecture Notes in Computer Science(), vol 10593. Springer, Cham. https://doi.org/10.1007/978-3-319-68759-9_61
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DOI: https://doi.org/10.1007/978-3-319-68759-9_61
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