Abstract
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.
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Notes
- 1.
In order to simplify the notation, we assume that for blasting activities we have a single machine \(r \in M_{blasting}\) with infinite capacity.
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This work was partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP).
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Åstrand, M., Johansson, M., Zanarini, A. (2018). Fleet Scheduling in Underground Mines Using Constraint Programming. In: van Hoeve, WJ. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2018. Lecture Notes in Computer Science(), vol 10848. Springer, Cham. https://doi.org/10.1007/978-3-319-93031-2_44
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