Optimization of Surface Mining Dig Limits with a Practical Heuristic Algorithm Mining, Metallurgy and Exploration

This paper presents an algorithm for optimizing the classification of surface mine material subject to excavating constraints. High-resolution expected profit models are input and optimized to classification maps subject to site-specific rectangular excavating constraints. This optimization problem defies traditional closed-form analytical solutions; a practical heuristic algorithm has been developed to quickly determine the optimal final destination for the material subject to realistic constraints. The optimization is fast and generates results that achieve up to 98–99% of the total expected profit achieved with free selection. This algorithm provides a fast viable option for practical application in short-term grade control and in managing multiple realizations in long-term resource estimation.