Abstract
The open pit mine block sequencing problem (OPBS) seeks a discretetime production schedule that maximizes the net present value of the orebody extracted from an open-pit mine. This integer program (IP) discretizes the mine’s volume into blocks, imposes precedence constraints between blocks, and limits resource consumption in each time period. We develop a “sliding time window heuristic” to solve this IP approximately. The heuristic recursively defines, solves and partially fixes an approximating model having: (i) fixed variables in early time periods, (ii) an exact submodel defined over a “window” of middle time periods, and (iii) a relaxed submodel in later time periods. The heuristic produces near-optimal solutions (typically within 2% of optimality) for model instances that standard optimization software fails to solve. Furthermore, it produces these solutions quickly, even though our OPBS model enforces standard upper-bounding constraints on resource consumption along with less standard, but important, lower-bounding constraints.
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We gratefully acknowledge the assistance of Professor Daniel Espinoza of the Universidad de Chile in running computation for upper bound verification.
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Cullenbine, C., Wood, R.K. & Newman, A. A sliding time window heuristic for open pit mine block sequencing. Optim Lett 5, 365–377 (2011). https://doi.org/10.1007/s11590-011-0306-2
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DOI: https://doi.org/10.1007/s11590-011-0306-2