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A Hard-Rock Mining Company Optimizes Schedules for Strategic Decision Making

John Ayaburi et al.

INFORMS Journal on Applied Analytics2026https://doi.org/10.1287/inte.2025.0200article
AJG 2
Weight
0.50

What the paper says

Our industry partner seeks an investment strategy and corresponding extraction schedule at daily fidelity of three-dimensional, notional blocks of ore (and waste) to maximize the discounted ounces of metal subject to spatial precedence, geotechnical, and operational constraints. This study develops an integer program, which we implement in Python, that enables fast parametric analysis, supports project-specific constraints, and generates (near-)optimal block schedules. Our model produces reliable and sustainable long-term scheduling solutions within five hours, which is faster than the time required for engineers to manually generate schedules and is acceptable for scenario analyses regarding changes in commodity price, crew productivity, plant sizing, and equipment availability.

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https://doi.org/https://doi.org/10.1287/inte.2025.0200

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@article{john2026,
  title        = {{A Hard-Rock Mining Company Optimizes Schedules for Strategic Decision Making}},
  author       = {John Ayaburi et al.},
  journal      = {INFORMS Journal on Applied Analytics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1287/inte.2025.0200},
}

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A Hard-Rock Mining Company Optimizes Schedules for Strategic Decision Making

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.