Heuristic rule for truck dispatching in open-pit mines with local information-based decisions

This paper proposes a new algorithm to make real time dispatching decisions in open-pit mines based on discrete position information. New methods are presented to estimate the probability density function for the position of each vehicle across the mine. New heuristic rules are then presented that use current local data gathered by peer to peer communication systems and vehicle position estimates to select the optimal destination and travel plan for each vehicle. A comparison of the algorithm with the existing approaches based on global information of truck position is presented. The results show that the performance improves using the discrete information, and there is significant improvements in the event of accidents or queuing.