Fleet Scheduling in Underground Mines Using Constraint Programming
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The profitability of an underground mine is greatly affected by the scheduling of the mobile production fleet. Today, most mine operations are scheduled manually, which is a tedious and error-prone activity. In this contribution, we present and formalize the underground mine scheduling problem, and propose a CP-based model for solving it. The model is evaluated on instances generated from real data. The results are promising and show a potential for further extensions.
This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP).
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