Abstract
The decreasing availability of resources amenable to surface operations has led to increasing numbers of underground mines, with trends indicating this will continue into the future. As a result, there is a need for additional optimization processes and techniques for underground mines, with many analogous methods having already been developed for surface mining. Current methods for design and optimization of stope boundary selection and scheduling mainly involve heuristic methods which focus on a single lever. Individual optimality may be approached, but globally optimal results can be obtained only by an integrated, rigorous approach. In this paper we review previous methodologies for stope boundary selection and medium- to long-term scheduling and highlight the need for an integrated approach. Previous integrated approaches are reviewed and an improved modelling system proposed for shorter solution times and greater applicability to mining situations. Randomly generated data-sets for gold-copper mineralization are used to investigate the model performance, describing solution time as a function of data complexity.
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