Application of Particle Swarm Optimization Algorithm to Optimize Stope Layout for Underground Mines

After the exploration phase, data collected are analyzed and interpreted using geostatistical modeling techniques to produce an orebody model. The orebody model is delineated into thousands of mining blocks in 3D space with assigned grade values. The geological information will inform the type of mining to be adopted, whether surface or underground mining. Consequently, the appropriate mining method is selected depending on the type of deposit. It is at this stage that mine planners can commence with the generation of an optimal stope layout subject to economic and technical constraints. The selection of an optimum stoping layout is one of the important areas of mine planning; however, it is still relatively underdeveloped. There are several algorithms that have been developed to generate a stope layout for underground mining. However, none of these algorithms guarantees an optimal solution in 3D. PSO has not been applied to the stope boundary problem, although its principles are amenable to the 3D environment. This begs the question: can the PSO algorithm generate an optimum 3D underground stope layout? This paper refers to part of an MSc research study undertaken at the University of the Witwatersrand.