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Cutoff Grade Optimization on Operative Decision Variables with Geological Uncertainty in an Underground Gold Mine: A Real Case Study

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  • Diego Alejandro Toro Morales

    (Facultad de Minas, Universidad Nacional de Colombia, Medellín 050041, Colombia)

  • Giovanni Franco Sepúlveda

    (Facultad de Minas, Universidad Nacional de Colombia, Medellín 050041, Colombia)

  • Erick de la Barra

    (School of Business, Universidad Católica del Norte, Coquimbo 1780000, Chile)

  • Juan Camilo Del Río Cuervo

    (Amazon Web Services (AWS), Seattle, WA 98109, USA)

Abstract

In mine planning, uncertainty assessment is essential to properly value a mining project. Geological, operational, and economical risks have to be considered to find the variable values that maximize the profit of the project. In this research, geological uncertainties are taken into account to assess the economic value of an underground gold mine. The scenarios considered are the tonnage-grade curves which are simulated by the Monte Carlo method. The decision variables are the cutoff grade (CoG), the Life of Mine (LoM), and operational variables, namely the mining and the processing capacity. In order to assess the economic value, we maximize the Net Present Value (NPV), which is carried out by a Genetic Algorithm (GA). This optimization, so-called implicit optimization, generates results of the probabilistic model which are compared with the deterministic one; the results found for a real underground gold mine show that, in the probabilistic case, the Net Present Value is higher and the time horizon is shorter than the results of the deterministic case, and the mining and the processing capacity are higher for the probabilistic case than the deterministic one.

Suggested Citation

  • Diego Alejandro Toro Morales & Giovanni Franco Sepúlveda & Erick de la Barra & Juan Camilo Del Río Cuervo, 2024. "Cutoff Grade Optimization on Operative Decision Variables with Geological Uncertainty in an Underground Gold Mine: A Real Case Study," Mathematics, MDPI, vol. 12(22), pages 1-16, November.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:22:p:3450-:d:1514277
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    References listed on IDEAS

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    1. Ahmadi, Mohammad Reza & Shahabi, Reza Shakoor, 2018. "Cutoff grade optimization in open pit mines using genetic algorithm," Resources Policy, Elsevier, vol. 55(C), pages 184-191.
    2. Oualid Benallou & Rajae Aboulaich, 2017. "Improving Capital Budgeting Through Probabilistic Approaches," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-21, September.
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