Abstract

ZENG, W.; BAAFI, E.Y.  and  FAN, H.. A simulation model to study truck-allocation options. J. S. Afr. Inst. Min. Metall. [online]. 2022, vol.122, n.12, pp.741-750. ISSN 2411-9717.  http://dx.doi.org/10.17159/2411-9717/2100/2022.

We present a discrete event simulator, TSJSim (Truck-Shovel JaamSim Simulator), for evaluating the stochastic and dynamic operational variables in a truck-shovel system. TSJSim offers four truck allocation strategies: Fixed truck assignment (FTA), Minimizing shovel production requirement (MSPR), Minimizing truck waiting time (MTWT), and Minimizing truck semi-cycle time (MTSCT) including the genetic algorithm (GA) optimization and the frozen dispatching algorithm (FDA) optimization rules. Multiple decision points along the haul routes for all the trucks close to the decision points were included in the model. The simulation results indicate that the trends associated with production tons and queuing time utilizing the four truck allocation strategies (MSPR, MTWT, FDA, and GA) all demonstrated similar patterns as the fleet size varied. As the system fleet size increased, the system production tons under these strategies at first increased significantly and then remained relatively constant; the queuing time relating to these strategies showed a positive relationship with the system fleet size. The bunching time decreased when the truck allocation strategies were applied in the model. In the simulated truck-shovel network system with multiple traffic intersections, by assigning the trucks at the intersections, both productivity and fleet utilization increased.

Keywords : truck-shovel system; simulation; truck allocation strategy; optimization.

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