Classical and stochastic mine planning techniques, state of the art and trends.
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Date
2018
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Abstract
Determination of the best possible ultimate pit for an open pit mine is a
fundamental subject that has undergone a highly evolutionary process, reviewed
in this study, since the correct choice carries substantial economic impact for the
industry. The correct choice can be very beneficial for project analysis, whereas
an incorrect choice has the potential to mask huge financial and economic future
losses that could render a project unfeasible. The advent of computers in the
1960s allowed sophisticated analysis for the selection of the best ultimate pit determination,
under specific modifying factors such as economic, social, environmental,
and political, but only in deterministic situations, i.e., when the problem
and variables for the ultimate pit determinations were considered deterministically
and almost always based on average values. Techniques such as the Lerchs–
Grossman algorithm and mixed-integer programming are among many standard
tools now used by the mineral industry. Geological uncertainty and the associated
risks as well as the need to consider the appropriate time to mine a block during
a mine operation have a significant impact on the net present value of the resulting
ultimate pits. Stochastic aspects embed a probabilistic component that varies
in time and are now under intense investigation by researchers, who are creating
algorithms that can be experimented with and tested in real mine situations. One
can expect that once these algorithms demonstrate their efficiency and superior
results, they will readily dominate the industry.
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Keywords
Deterministic mine planning, Direct block schedule, Uncertainty
Citation
TORRES, V. F. N. et al. Classical and stochastic mine planning techniques, state of the art and trends. REM - International Engineering Journal, v. 71, p. 289-297, 2018. Disponível em: <http://www.scielo.br/scielo.php?script=sci_abstract&pid=S2448-167X2018000200289&lng=en&nrm=iso>. Acesso em: 12 fev. 2019.