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Optimized open pit mine design, pushbacks and the gap problem—a review

Conor MeagherCOSMO-Stochastic Mine Planning Laboratory, Department of Mining and Materials Engineering, McGill University, FDA Building, 3450 University Street, Montreal, Quebec, H3A 2T5, CanadaRoussos DimitrakopoulosCOSMO-Stochastic Mine Planning Laboratory, Department of Mining and Materials Engineering, McGill University, FDA Building, 3450 University Street, Montreal, Quebec, H3A 2T5, CanadaDavid AvisCOSMO-Stochastic Mine Planning Laboratory, Department of Mining and Materials Engineering, McGill University, FDA Building, 3450 University Street, Montreal, Quebec, H3A 2T5, Canada

2014en

ABI

Annotatsiya

Existing methods of pushback (phase) design are reviewed in the context of “gap” problems, a term used to describe inconsistent sizes between successive pushbacks. Such gap problems lead to suboptimal open pit mining designs in terms of maximizing net present value. Methods such as the Lerchs-Grossman algorithm, network flow techniques, the fundamental tree algorithm, and Seymour’s parameterized pit algorithm are examined to see how they can be used to produce pushback designs and how they address gap issues. Areas of current and future research on producing pushbacks with a constrained size to help eliminate gap problems are discussed. A framework for incorporating discounting at the time of pushback design is proposed, which can lead to mine designs with increased NPV.

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DOI: 10.1134/s1062739114030132

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