Short-term mine production scheduling for industrial minerals using multi-objective simulated annealing

Abstract

The in-situ mineral characteristics of a deposit are simulated by sequential co-simulation and averaging the simulated characteristics within specified block volumes creates a three-dimensional block model. This model is then submitted to optimal open pit and production scheduling algorithms. As the market values of industrial minerals depend on the satisfaction of predetermined blending criteria rather than metal content, a Linear Programming (LP) scheme has been used to identify all blocks that can be included in the blend without violating the grade requirements. The Lerchs-Grosmann algorithm using the blocks identified by the LP program determines optimal pit limits. All blocks that lie outside the optimal pit are removed from the system and the blocks within the optimal pit are submitted to the production-scheduling algorithm. Production scheduling optimisation is done in two stages: Lagrangean parameterisation, resulting in an initial sub-optimal solution, and multi-objective simulated annealing (MOSA) improving the sub-optimal schedule further.