A heuristic algorithm to optimise stope boundaries

Determination of the optimum mine layout is one of the important tasks in mine planning. In the case of open pit mines, a large number of algorithms using a range of techniques have been developed to generate the true optimum solution. Several commercial computer packages are available to assist mining engineers design open pits. In contrast, only a few algorithms, using limited techniques, have been developed to optimise the stope geometry in underground operations. Most of which fail to provide optimum 3D solutions. A heuristic algorithm, termed the "Maximum Value Neighbourhood" (MVN) was developed in this thesis to optimise stope boundaries. The MVN algorithm benefits from its simplicity in both concept and implementation. It provides a 3D analysis and can be applied to any underground mining method, although it does not guarantee the true "optimum" stope layout. The MVN algorithm uses a 3D fixed economic block model to locate the best neighbourhood of a block, which guarantees the maximum net value. Neighbourhoods are restricted by the mine geometry constraints. The neighbourhood concept is based on the number of mining blocks equivalent to the minimum stope size. Since a variety of neighbourhoods are available for each block, the one that provides the maximum net value (the maximum value neighbourhood, MVN) is located for inclusion in the final stope. In order to test the algorithm, the 3D version of the MVN algorithm was implemented on small sized examples, using the Visual Basic for Applications (VBA) modules supported by Microsoft Excel. The framework of the Excel worksheets was suitable to store block data and display the optimised stope. A Fortran 90 program, the "Stope Limit Optimiser" (SLO), was developed to implement the 3 D MVN algorithm on actual mine data. The SLO optimiser integrates