Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo
ABSTRACT : This study presents a method for feature selection in datasets that suffer from high dimensionality, aimed at evaluating relative efficiency using the nonparametric technique known as Data Envelopment Analysis (DEA). This application is implemented using genetic algorithms for multi-objec...
- Autores:
-
Ramírez Upegui, Nelson Fabián
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2024
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- spa
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/44515
- Acceso en línea:
- https://hdl.handle.net/10495/44515
- Palabra clave:
- Análisis de datos
Data analysis
Algoritmos genéticos
Genetic algorithms
Optimización combinatoria
Combinatorial optimization
http://vocabularies.unesco.org/thesaurus/concept2214
- Rights
- openAccess
- License
- https://creativecommons.org/licenses/by-nc-sa/4.0/
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| dc.title.spa.fl_str_mv |
Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo |
| title |
Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo |
| spellingShingle |
Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo Análisis de datos Data analysis Algoritmos genéticos Genetic algorithms Optimización combinatoria Combinatorial optimization http://vocabularies.unesco.org/thesaurus/concept2214 |
| title_short |
Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo |
| title_full |
Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo |
| title_fullStr |
Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo |
| title_full_unstemmed |
Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo |
| title_sort |
Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivo |
| dc.creator.fl_str_mv |
Ramírez Upegui, Nelson Fabián |
| dc.contributor.advisor.none.fl_str_mv |
Villegas Ramirez, Juan Guillermo |
| dc.contributor.author.none.fl_str_mv |
Ramírez Upegui, Nelson Fabián |
| dc.subject.unesco.none.fl_str_mv |
Análisis de datos Data analysis |
| topic |
Análisis de datos Data analysis Algoritmos genéticos Genetic algorithms Optimización combinatoria Combinatorial optimization http://vocabularies.unesco.org/thesaurus/concept2214 |
| dc.subject.lemb.none.fl_str_mv |
Algoritmos genéticos Genetic algorithms Optimización combinatoria Combinatorial optimization |
| dc.subject.unescouri.none.fl_str_mv |
http://vocabularies.unesco.org/thesaurus/concept2214 |
| description |
ABSTRACT : This study presents a method for feature selection in datasets that suffer from high dimensionality, aimed at evaluating relative efficiency using the nonparametric technique known as Data Envelopment Analysis (DEA). This application is implemented using genetic algorithms for multi-objective optimization, applying a basic binary structure to select the variables from the dataset that will enter the DEA evaluation. The selection process is carried out through crossover and mutation of an initially randomly selected population from the solution space. Four different well-known multiobjective genetic algorithms are used and compared using data sets from the DEA literature. |
| publishDate |
2024 |
| dc.date.issued.none.fl_str_mv |
2024 |
| dc.date.accessioned.none.fl_str_mv |
2025-01-29T16:45:01Z |
| dc.date.available.none.fl_str_mv |
2025-01-29T16:45:01Z |
| dc.type.spa.fl_str_mv |
Artículo de investigación |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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https://purl.org/redcol/resource_type/ART |
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http://purl.org/coar/version/c_b1a7d7d4d402bcce |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/draft |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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draft |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/10495/44515 |
| url |
https://hdl.handle.net/10495/44515 |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.rights.uri.spa.fl_str_mv |
https://creativecommons.org/licenses/by-nc-sa/4.0/ |
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info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by-nc-sa/4.0/ http://purl.org/coar/access_right/c_abf2 |
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openAccess |
| dc.format.extent.spa.fl_str_mv |
19 páginas |
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application/pdf |
| dc.publisher.spa.fl_str_mv |
Universidad de Antioquia |
| dc.publisher.place.spa.fl_str_mv |
Medellín, Colombia |
| dc.publisher.faculty.spa.fl_str_mv |
Facultad de Ingeniería. Especialización en Analítica y Ciencia de Datos |
| institution |
Universidad de Antioquia |
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Villegas Ramirez, Juan GuillermoRamírez Upegui, Nelson Fabián2025-01-29T16:45:01Z2025-01-29T16:45:01Z2024https://hdl.handle.net/10495/44515ABSTRACT : This study presents a method for feature selection in datasets that suffer from high dimensionality, aimed at evaluating relative efficiency using the nonparametric technique known as Data Envelopment Analysis (DEA). This application is implemented using genetic algorithms for multi-objective optimization, applying a basic binary structure to select the variables from the dataset that will enter the DEA evaluation. The selection process is carried out through crossover and mutation of an initially randomly selected population from the solution space. Four different well-known multiobjective genetic algorithms are used and compared using data sets from the DEA literature.EspecializaciónEspecialista en Analítica y Ciencia de Datos19 páginasapplication/pdfspaUniversidad de AntioquiaMedellín, ColombiaFacultad de Ingeniería. Especialización en Analítica y Ciencia de Datoshttps://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Selección de entradas y salidas en DEA mediante algoritmos genéticos multiobjetivoArtículo de investigaciónhttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_b1a7d7d4d402bcceinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/draftAnálisis de datosData analysisAlgoritmos genéticosGenetic algorithmsOptimización combinatoriaCombinatorial optimizationhttp://vocabularies.unesco.org/thesaurus/concept2214PublicationORIGINALRamirezNelson_2024_SelecciónCaracterísticasAG.pdfRamirezNelson_2024_SelecciónCaracterísticasAG.pdfTrabajo de grado de especializaciónapplication/pdf1751464https://bibliotecadigital.udea.edu.co/bitstreams/f9d5bfb6-02f4-4b4e-998e-1547f3e74e7b/download4cb14b061a8e8dadc7a616b9091c6cc1MD55trueAnonymousREADLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://bibliotecadigital.udea.edu.co/bitstreams/39c05b7e-6b87-4306-aa36-c5c0c734247d/download8a4605be74aa9ea9d79846c1fba20a33MD56falseAnonymousREADTEXTRamirezNelson_2024_SelecciónCaracterísticasAG.pdf.txtRamirezNelson_2024_SelecciónCaracterísticasAG.pdf.txtExtracted texttext/plain84262https://bibliotecadigital.udea.edu.co/bitstreams/273ec828-fa4f-4439-9f81-7b223354e4eb/download6fa5e732fb925935f54895d1051b6989MD57falseAnonymousREADTHUMBNAILRamirezNelson_2024_SelecciónCaracterísticasAG.pdf.jpgRamirezNelson_2024_SelecciónCaracterísticasAG.pdf.jpgGenerated Thumbnailimage/jpeg6263https://bibliotecadigital.udea.edu.co/bitstreams/4283aafa-161c-45b9-a72b-559866c74e8c/download944bf79bd183d6d9289e9fb006e7d999MD58falseAnonymousREAD10495/44515oai:bibliotecadigital.udea.edu.co:10495/445152025-03-27 00:23:04.219https://creativecommons.org/licenses/by-nc-sa/4.0/open.accesshttps://bibliotecadigital.udea.edu.coRepositorio Institucional de la Universidad de Antioquiaaplicacionbibliotecadigitalbiblioteca@udea.edu.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 |