Financially Efficient Dig-Line Delineation Incorporating Equipment Constraints and Grade Uncertainty

Abstract

Greedy local search heuristics that provide estimates of financially efficient dig-lines are proposed. To generate alternate dig-lines these heuristics employ a floating circle-based perturbation mechanism that ensures that mining equipment constraints are satisfied. Distributions of financial payoffs for alternate dig-lines are constructed from multiple conditional simulations, then evaluated using a mean-downside risk efficiency model. Computational results show that equipment constraints significantly increase the financial risk for a given expected payoff and that the heuristic efficient frontier is sensitive to the mining strategy. For the problem instances that we examined we observed that mining waste material at transitions prior to mining ore material: minimised the upfront operating costs; maximised the profit for a given level of financial risk; and freed milling capacity.

Keywords:

• conditional simulation
• portfolio theory
• floating cone
• combinatorial optimisation
• local search heuristic
• open pit mining