Efficient simulation for an open-pit mine

This paper presents an approach towards computationally efficient discrete-event-simulation designed to take advantage of high-performance computing architecture. We demonstrate how computational efficiency combined with large computing capacity enables quantification and mapping of stochastic system performance across a computationally challenging multidimensional parameter space requiring several million individual DES instances. An open-pit mine bulk materials handling system case study is presented to demonstrate the approach. A dispatching heuristic controlling the operation of the trucking system can be optimised through the selection of values for four control parameters. The multidimensional space represented by these control parameters is exhaustively mapped and visualised to provide insight into the relationships between combinations of parameters and system performance. The extensive data generated is ultimately used within a hyper-heuristic to determine near-optimal values for the dispatching heuristic control parameters.