Search

Optimisation of three-dimensional (3D) underground stope layouts is a computationally complex process since it involves the modelling of many variables and constraints. As the number of variables and constraints increases to reflect the actual mining practice, the model complexity and solution time tend to increase exponentially, making the optimisation problem intractable. Metaheuristic approaches have therefore been used predominantly to solve the problem, but do not guarantee 'true' optimality. To minimise this limitation, a dual interchange algorithm (DIA) was developed by combining the strengths of two metaheuristic generic algorithms, namely the particle swarm optimisation (PSO) and genetic algorithm (GA). The DIA performance was compared to that of the Mineable Shape Optimizer (MSO) on four different design scenarios. The DIA generated stope layout economic values (SLEV) for three scenarios which were 0.3%, 3.4%, and 8.3% higher than for MSO under fixed and variable stope width conditions, while MSO produced a SLEV which was 9.7% higher than the DIA for a fixed stope width. This paper demonstrates that the DIA is a novel way of solving 3D optimisation of stope layouts under variable stope widths as encountered in actual mining practice. [ABSTRACT FROM AUTHOR]