A decomposition approach for correlated random vector generation

"When doing simulation studies, it is necessary to consider correlation in input variables in order to obtain correct results. Generating correlated random nurnbers is not always an easy task, as the accuracy and computational stability of some methods depend of the probabilit, y distribution o...

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Autores:
Guaje Acosta, Oscar Orlando
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
spa
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/61040
Acceso en línea:
http://hdl.handle.net/1992/61040
Palabra clave:
Correlación (Estadística)
Métodos de simulación
Optimización matemática
Rights
openAccess
License
https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
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spelling Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdfinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Medaglia González, Andrés L163ee545-71d0-42a2-8b75-61c957347fb6500Guaje Acosta, Oscar Orlando26871500Mura, IvanSefair Cristancho, Jorge Alberto2022-09-26T22:07:46Z2022-09-26T22:07:46Z2016http://hdl.handle.net/1992/61040instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/754062-1001"When doing simulation studies, it is necessary to consider correlation in input variables in order to obtain correct results. Generating correlated random nurnbers is not always an easy task, as the accuracy and computational stability of some methods depend of the probabilit, y distribution of input variables. We present a method based on mixed-integer programrning to generate correlated random numbers. Since this method does not perform acceptably, we show a column generation procedure used to accelerate the MIP. We implemented our method and found significant computational improvements over the base MIP while improving the accuracy of the solution over known methods.".-- Tomado del resumen.Magíster en Ingeniería IndustrialMaestría23 hojasapplication/pdfspaUniversidad de los AndesMaestría en Ingeniería IndustrialFacultad de IngenieríaDepartamento de Ingeniería IndustrialA decomposition approach for correlated random vector generationTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMCorrelación (Estadística)Métodos de simulaciónOptimización matemática200714242PublicationTEXT11314.pdf.txt11314.pdf.txtExtracted texttext/plain38632https://repositorio.uniandes.edu.co/bitstreams/ef9838e2-a426-44dd-8667-ce3da179273c/downloadb7bb00be00bb36745511021347d67515MD52ORIGINAL11314.pdfapplication/pdf456160https://repositorio.uniandes.edu.co/bitstreams/dfe7a19e-e129-4886-8fb8-356b7df6c396/downloadec01e0e9e8240da27f819684acdd8595MD51THUMBNAIL11314.pdf.jpg11314.pdf.jpgIM Thumbnailimage/jpeg5606https://repositorio.uniandes.edu.co/bitstreams/1eb6450a-d665-4d77-908b-fd2c0aea1f93/download94a5f0c17ece179cfcfd88483604959fMD531992/61040oai:repositorio.uniandes.edu.co:1992/610402023-10-10 17:23:27.247https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdfopen.accesshttps://repositorio.uniandes.edu.coRepositorio institucional Sénecaadminrepositorio@uniandes.edu.co
dc.title.spa.fl_str_mv A decomposition approach for correlated random vector generation
title A decomposition approach for correlated random vector generation
spellingShingle A decomposition approach for correlated random vector generation
Correlación (Estadística)
Métodos de simulación
Optimización matemática
title_short A decomposition approach for correlated random vector generation
title_full A decomposition approach for correlated random vector generation
title_fullStr A decomposition approach for correlated random vector generation
title_full_unstemmed A decomposition approach for correlated random vector generation
title_sort A decomposition approach for correlated random vector generation
dc.creator.fl_str_mv Guaje Acosta, Oscar Orlando
dc.contributor.advisor.none.fl_str_mv Medaglia González, Andrés L
dc.contributor.author.none.fl_str_mv Guaje Acosta, Oscar Orlando
dc.contributor.jury.none.fl_str_mv Mura, Ivan
Sefair Cristancho, Jorge Alberto
dc.subject.keyword.spa.fl_str_mv Correlación (Estadística)
Métodos de simulación
Optimización matemática
topic Correlación (Estadística)
Métodos de simulación
Optimización matemática
description "When doing simulation studies, it is necessary to consider correlation in input variables in order to obtain correct results. Generating correlated random nurnbers is not always an easy task, as the accuracy and computational stability of some methods depend of the probabilit, y distribution of input variables. We present a method based on mixed-integer programrning to generate correlated random numbers. Since this method does not perform acceptably, we show a column generation procedure used to accelerate the MIP. We implemented our method and found significant computational improvements over the base MIP while improving the accuracy of the solution over known methods.".-- Tomado del resumen.
publishDate 2016
dc.date.issued.spa.fl_str_mv 2016
dc.date.accessioned.none.fl_str_mv 2022-09-26T22:07:46Z
dc.date.available.none.fl_str_mv 2022-09-26T22:07:46Z
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
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dc.format.extent.spa.fl_str_mv 23 hojas
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dc.publisher.spa.fl_str_mv Universidad de los Andes
dc.publisher.program.spa.fl_str_mv Maestría en Ingeniería Industrial
dc.publisher.faculty.spa.fl_str_mv Facultad de Ingeniería
dc.publisher.department.spa.fl_str_mv Departamento de Ingeniería Industrial
institution Universidad de los Andes
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