Classical and stochastic mine planning techniques, state of the art and trends.

dc.contributor.authorTorres, Vidal Félix Navarro
dc.contributor.authorNader, Beck
dc.contributor.authorArroyo Ortiz, Carlos Enrique
dc.contributor.authorSouza, Felipe Ribeiro
dc.contributor.authorBurgarelli, Hudson Rodrigues
dc.contributor.authorChaves, Leonardo Soares
dc.contributor.authorCarvalho, Luiz Alberto de
dc.contributor.authorCâmara, Taís Renata
dc.contributor.authorFernandes, Eunírio Zanetti
dc.contributor.authorGalery, Roberto
dc.date.accessioned2019-05-10T12:17:40Z
dc.date.available2019-05-10T12:17:40Z
dc.date.issued2018
dc.description.abstractDetermination 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.pt_BR
dc.identifier.citationTORRES, 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.pt_BR
dc.identifier.doihttp://dx.doi.org/10.1590/0370-44672016710165pt_BR
dc.identifier.issn1807-0353
dc.identifier.urihttp://www.repositorio.ufop.br/handle/123456789/11264
dc.language.isoen_USpt_BR
dc.rightsabertopt_BR
dc.rights.licenseA REM - International Engineering Journal - autoriza o depósito de cópia de artigos dos professores e alunos da UFOP no Repositório Institucional da UFOP. Licença concedida mediante preenchimento de formulário online em 12 set. 2013.pt_BR
dc.subjectDeterministic mine planningpt_BR
dc.subjectDirect block schedulept_BR
dc.subjectUncertaintypt_BR
dc.titleClassical and stochastic mine planning techniques, state of the art and trends.pt_BR
dc.typeArtigo publicado em periodicopt_BR

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