Optimising Stope Sequences for Long Term Mine Planning

Long-term mine scheduling is one of the most difficult optimization problems. The problem is said to be NP-complete in that the best possible solution cannot be found any quicker than checking all possible permutations and combinations. Although a number of techniques have been used in the past, many include significant simplifications or fail to produce acceptable results within the required timeframe. Genetic Algorithms (GAs) are among the most promising optimisation techniques within operations research. They are based on natural selection and evolution of solutions to complex problems. They have been known to quickly converge within a few percent of the optimal solution by examining only a fraction of the solution search space. The GA itself contains very little problem specific information and as such, has been linked to a discrete-event simulation (DES). The DES feeds information regarding the feasibility and quality of the solutions back to the GA during the optimisation process. In this paper, GAs and DES are described and the coupling of the two methods is outlined. The GA coupled DES is then used to ?optimise? a problem and the results are discussed.