A linkage of truck-and-shovel operations to short-term mine plans using discrete-event simulation

Abstract

The economics of today's mining industry requires more efficient usage of truck-shovel systems. In this paper, a discrete-event simulation model is developed, implemented, and verified to analyse the behaviour of a stochastic truck-shovel materials-handling and haulage system in open-pit mining. A mixed integer linear programming model (MILP) is also developed to deal with the allocation problem in which trucks and shovels are assigned to mining faces. The simulation model is linked to the optimal short-term mine production schedule generated by mathematical programming using exact solution methodology. The simulation model imitates the complex truck-shovel system, and considers the uncertainties associated with the operations of trucks and shovels. The simulation model provides a tool to improve the system's efficiency, and guarantees that the operational plans will honour the optimum net present value obtained in the production-scheduling phase.