Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera

ilustraciones, diagramas

Autores:
Toro Morales, Diego Alejandro
Tipo de recurso:
Fecha de publicación:
2023
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/84945
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/84945
https://repositorio.unal.edu.co/
Palabra clave:
620 - Ingeniería y operaciones afines::622 - Minería y operaciones relacionadas
Minas de oro
Gold mines and mining
optimización estocástica
ley de corte
Valor Presente Neto
Algoritmos Genéticos
minería subterránea
oro
stochastic optimization
cut-off grade
Net Present Value
Genetic Algorithms
underground mining
gold
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
id UNACIONAL2_98eec30a3df2bdc4925a9d3fd50995b9
oai_identifier_str oai:repositorio.unal.edu.co:unal/84945
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera
dc.title.translated.eng.fl_str_mv Stochastic optimization model of cut-off grades for a gold mining company
title Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera
spellingShingle Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera
620 - Ingeniería y operaciones afines::622 - Minería y operaciones relacionadas
Minas de oro
Gold mines and mining
optimización estocástica
ley de corte
Valor Presente Neto
Algoritmos Genéticos
minería subterránea
oro
stochastic optimization
cut-off grade
Net Present Value
Genetic Algorithms
underground mining
gold
title_short Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera
title_full Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera
title_fullStr Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera
title_full_unstemmed Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera
title_sort Modelo de optimización estocástica de leyes de corte para una compañía minera aurífera
dc.creator.fl_str_mv Toro Morales, Diego Alejandro
dc.contributor.advisor.none.fl_str_mv Franco Sepúlveda, Giovanni
Del Rio Cuervo, Juan Camilo
dc.contributor.author.none.fl_str_mv Toro Morales, Diego Alejandro
dc.contributor.orcid.spa.fl_str_mv Franco Sepúlveda, Giovanni [0000-0003-4579-8389]
Del Rio Cuervo, Juan Camilo [0000-0003-0091-354X]
dc.subject.ddc.spa.fl_str_mv 620 - Ingeniería y operaciones afines::622 - Minería y operaciones relacionadas
topic 620 - Ingeniería y operaciones afines::622 - Minería y operaciones relacionadas
Minas de oro
Gold mines and mining
optimización estocástica
ley de corte
Valor Presente Neto
Algoritmos Genéticos
minería subterránea
oro
stochastic optimization
cut-off grade
Net Present Value
Genetic Algorithms
underground mining
gold
dc.subject.lemb.spa.fl_str_mv Minas de oro
dc.subject.lemb.eng.fl_str_mv Gold mines and mining
dc.subject.proposal.spa.fl_str_mv optimización estocástica
ley de corte
Valor Presente Neto
Algoritmos Genéticos
minería subterránea
oro
dc.subject.proposal.eng.fl_str_mv stochastic optimization
cut-off grade
Net Present Value
Genetic Algorithms
underground mining
gold
description ilustraciones, diagramas
publishDate 2023
dc.date.accessioned.none.fl_str_mv 2023-11-14T19:54:48Z
dc.date.available.none.fl_str_mv 2023-11-14T19:54:48Z
dc.date.issued.none.fl_str_mv 2023-11-09
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/TM
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/84945
dc.identifier.instname.spa.fl_str_mv Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv https://repositorio.unal.edu.co/
url https://repositorio.unal.edu.co/handle/unal/84945
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.indexed.spa.fl_str_mv RedCol
LaReferencia
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dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
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dc.format.extent.spa.fl_str_mv xiv, 100 páginas
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dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv Medellín - Minas - Maestría en Ingeniería - Recursos Minerales
dc.publisher.faculty.spa.fl_str_mv Facultad de Minas
dc.publisher.place.spa.fl_str_mv Medellín, Colombia
dc.publisher.branch.spa.fl_str_mv Universidad Nacional de Colombia - Sede Medellín
institution Universidad Nacional de Colombia
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spelling Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Franco Sepúlveda, Giovanni8fa3f0b6d38e1f9e02674136a820e381Del Rio Cuervo, Juan Camilo4a94ca842a25e86396205ab9083877b1Toro Morales, Diego Alejandro48be3b6c212aa74891f374bd9a11dd10Franco Sepúlveda, Giovanni [0000-0003-4579-8389]Del Rio Cuervo, Juan Camilo [0000-0003-0091-354X]2023-11-14T19:54:48Z2023-11-14T19:54:48Z2023-11-09https://repositorio.unal.edu.co/handle/unal/84945Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasUna de las variables de decisión más estudiada en la bibliografía técnica minera en relación con su estimación y optimización es la ley de corte, en la que la función objetivo más aceptada ha sido la maximización del Valor Presente Neto (VPN). Sin embargo, un número considerable de proyectos mineros determinan sus leyes de corte a través del uso de modelos determinísticos que no permiten realizar un análisis basado en la incertidumbre. En el presente trabajo se formula un modelo de optimización estocástica de leyes de corte para un depósito aurífero, considerando los riesgos e incertidumbres propias de la actividad minera, con el propósito de maximizar el VPN del proyecto de una compañía con operaciones mineras subterráneas. La metodología seleccionada para el modelo corresponde a la optimización estocástica implícita, que utiliza un enfoque híbrido el cual combina un algoritmo metaheurístico (Algoritmo Genético) y la simulación de Montecarlo. La validación del modelo se realizó utilizando datos reales para verificar su aplicabilidad industrial y proporcionar una alternativa a los modelos tradicionales comúnmente utilizados hasta la fecha. El modelo formulado presentó una vida más corta del proyecto y una ley de corte dinámica en el tiempo, lo que se traduce en ingresos anuales variables. En cuanto a rentabilidad, se presentó un incremento de 21,142,372 USD al comparar la media del VPN del modelo estocástico con el VPN del modelo determinístico. Los resultados obtenidos demuestran los beneficios de aplicar este tipo de modelos a escala industrial para aumentar el valor de los proyectos. (Texto tomado de la fuente]One of the most studied decision variables in the technical mining literature regarding its estimation and optimization is the cut-off grade, where the most accepted objective function has been the maximization of NPV (Net Present Value). However, a considerable number of mining projects determine their cut-off grades using deterministic models that do not facilitate analysis based on uncertainty. In this study, a stochastic optimization model for cut-off grades is formulated for a gold deposit, taking into account the risks and uncertainties inherent in mining activities, with the purpose of maximizing the project's NPV for a company with underground mining operations. The selected methodology for the model is implicit stochastic optimization, employing a hybrid approach that combines a metaheuristic algorithm (Genetic Algorithm) and Monte Carlo simulation. The model's validation is conducted using real data to verify its industrial applicability and to offer an alternative to the commonly employed traditional models. The formulated model exhibits a shorter project life and a dynamic cut-off grade over time, resulting in variable annual revenues. Regarding profitability, a 21,142,372 USD increase is observed when comparing the mean NPV of the stochastic model with that of the deterministic model. These findings demonstrate the advantages of applying such models on an industrial scale to enhance project value.MaestríaMagíster en Ingeniería – Recursos MineralesPlaneamiento minero estocástico y optimización mineraÁrea Curricular de Recursos Mineralesxiv, 100 páginasapplication/pdfspaUniversidad Nacional de ColombiaMedellín - Minas - Maestría en Ingeniería - Recursos MineralesFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín620 - Ingeniería y operaciones afines::622 - Minería y operaciones relacionadasMinas de oroGold mines and miningoptimización estocásticaley de corteValor Presente NetoAlgoritmos Genéticosminería subterráneaorostochastic optimizationcut-off gradeNet Present ValueGenetic Algorithmsunderground mininggoldModelo de optimización estocástica de leyes de corte para una compañía minera auríferaStochastic optimization model of cut-off grades for a gold mining companyTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMRedColLaReferenciaAbdel Sabour, S. 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Mining, Metallurgy & Exploration, 36, 683–699.EstudiantesInvestigadoresMaestrosORIGINAL1037648048.2023.pdf1037648048.2023.pdfTesis de Maestría en Ingeniería - Recursos Mineralesapplication/pdf1864137https://repositorio.unal.edu.co/bitstream/unal/84945/4/1037648048.2023.pdfda83e70ca8fa8e67a80f472cb7373c97MD54LICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/84945/5/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD55THUMBNAIL1037648048.2023.pdf.jpg1037648048.2023.pdf.jpgGenerated Thumbnailimage/jpeg4671https://repositorio.unal.edu.co/bitstream/unal/84945/6/1037648048.2023.pdf.jpgf73e1db945b7d70e88ce6de090ea510dMD56unal/84945oai:repositorio.unal.edu.co:unal/849452024-08-19 23:10:59.907Repositorio Institucional Universidad Nacional de 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