CONCLUSIONS The integration of a stochastic optimization approach in short-term dispatch activities is a procedure to assess the operational risk in implemented Fleet Management Systems. It represents an opportunity to properly understand the implications of geological uncertainty, fleet performance variability, disruption events, and other aspects of the mine in the live dispatching of the truck fleet and shovel assignments. As short-term planning is usually focused on block scheduling, digging direction, and ore control methods, the daily plans rely heavily on the accuracy of the grade estimates of the ore blocks scheduled for blasting, which cannot be fully confirmed even after the material is delivered at its destination, and can involve shovel reallocations and truck rerouting in the worst-case scenarios. The proposed methodology offers a means of assessing and to decreasing the operational and economic risks of geologic uncertainty, while enhancing the capabilities of the installed Fleet Management System. Since truck dispatch optimization is sensitive to uncertainty factors in the short-term production plans, it should be optimized simultaneously with shovel allocation to create a baseline for a reliable live dispatching plan implementation. By observing the uncertain and variable nature of the short-term activities at an open pit mining operation, this methodology is well suited, offering a fleet plan based on a probabilistic assessment among multiples scenarios of occurrence, while also foreseeing the best course of action for possible outcomes and preventing high-risk decisions in the daily activities. ACKNOWLEDGEMENTS This project was undertaken thanks to funding from IVADO and the Canada First Research Excellence Fund. REFERENCES Afrapoli, A.M., Tabesh, M., & Askari-Nasab H. (2018). A Transportation Problem-Based Stochastic Integer Programming Model to Dispatch Surface Mining Trucks Under Uncertainty. Proceedings of the 27th International Symposium on Mine Planning and Equipment Selection - MPES 2018. p. 255-264. Ahumada, G.I., Riveros, E., & Herzog, O. (2020). An agent-based system for truck dispatching in open-pit mines. ICAART (1): 73-81. Alarie, S., & Gamache, M. (2002). Overview of solution strategies used in truck dispatching systems for open pit mines. International Journal of Surface Mining, Reclamation and Environment 16(1): 59-76. Bakhtavar, E., & Mahmoudi, H. (2018). Development of a scenario-based robust model for the optimal truck-shovel allocation in open-pit mining. Computers & Operations Research 115. Both, C., & Dimitrakopoulos, R. (2020). Joint stochastic short-term production scheduling and fleet management optimization for mining complexes. Optimization and Engineering, 21(4), 1717-1743.
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