Abstract:
Traditional mining selection methods focus on local estimates or loss functions that do not take into account the potential diversification benefits of financial risk that is unique to each location. A constrained efficient set model with a downside risk function is formulated as a solution. Estimates of this nonlinear mixed-integer combinatorial optimization problem are provided by a simulated annealing heuristic. A utility framework that is congruent with the proposed efficiency model is then used to choose the optimal set of local mining selections for a decision-maker with specific risk-averse characteristics. The methodology is demonstrated in a grade control environment. The results show that downside financial risk can be reduced by around 33% while the expected payoff is only reduced by 1% when compared to ore selections generated by traditional cut-off grade techniques.