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Ultimate open pit stochastic optimization

Denis Marcotte et Josiane Caron

Article de revue (2013)

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Abstract

Classical open pit optimization (maximum closure problem) is made on block estimates, without directly considering the block grades uncertainty. We propose an alternative approach of stochastic optimization. The stochastic optimization is taken as the optimal pit computed on the block expected profits, rather than expected grades, computed from a series of conditional simulations. The stochastic optimization generates, by construction, larger ore and waste tonnages than the classical optimization. Contrary to the classical approach, the stochastic optimization is conditionally unbiased for the realized profit given the predicted profit. A series of simulated deposits with different variograms are used to compare the stochastic approach, the classical approach and the simulated approach that maximizes expected profit among simulated designs. Profits obtained with the stochastic optimization are generally larger than the classical or simulated pit. The main factor controlling the relative gain of stochastic optimization compared to classical approach and simulated pit is shown to be the information level as measured by the boreholes spacing/range ratio. The relative gains of the stochastic approach over the classical approach increase with the treatment costs but decrease with mining costs. The relative gains of the stochastic approach over the simulated pit approach increase both with the treatment and mining costs. At early stages of an open pit project, when uncertainty is large, the stochastic optimization approach appears preferable to the classical approach or the simulated pit approach for fair comparison of the values of alternative projects and for the initial design and planning of the open pit.

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Matériel d'accompagnement:
Département: Département des génies civil, géologique et des mines
Organismes subventionnaires: NSERC, FRQNT
URL de PolyPublie: https://publications.polymtl.ca/13491/
Titre de la revue: Computers & Geosciences (vol. 51)
Maison d'édition: Elsevier
DOI: 10.1016/j.cageo.2012.08.008
URL officielle: https://doi.org/10.1016/j.cageo.2012.08.008
Date du dépôt: 18 avr. 2023 15:09
Dernière modification: 27 mars 2026 10:25
Citer en APA 7: Marcotte, D., & Caron, J. (2013). Ultimate open pit stochastic optimization. Computers & Geosciences, 51, 238-246. https://doi.org/10.1016/j.cageo.2012.08.008

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