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Selección óptima del portafolio de proyectos utilizando metaheurísticas de población y trayectoria meta-optimizadas

dc.contributor.authorCandia García, Cristian David
dc.contributor.authorLópez Castro, Luis Francisco
dc.contributor.authorJaimes Suárez, Sonia Alexandra
dc.date.accessioned2021-06-18T22:50:03Z
dc.date.accessioned2021-10-01T17:37:38Z
dc.date.available2021-06-18T22:50:03Z
dc.date.available2021-10-01T17:37:38Z
dc.date.issued2020
dc.identifier.issn1794-1237
dc.identifier.issn2463-0950
dc.identifier.urihttps://repositorio.escuelaing.edu.co/handle/001/1590
dc.description.abstractEste artículo aborda el problema de selección de portafolio de proyectos para la adjudicación de interventorías de obra pública a través de concursos de méritos abiertos (CMA) supervi-sados por el Instituto Nacional de Vías (INVIAS) en Colombia. En esta modalidad, cada con-cursante presenta un portafolio único de proyectos históricos para cuantificar su experiencia como interventor. Como alternativa al uso de hojas de cálculo en Excel con procedimientos limitados de enumeración exhaustiva, se evaluó un algoritmo genético meta-optimizado (GA) y un procedimiento de búsqueda voraz adaptativo probabilista meta-optimizado (GRASP) para el caso de estudio de una Compañía con 207 contratos de trayectoria en el sector. Ambas metaheurísticas consiguieron encontrar puntajes de valoración óptimos para distintas instancias de prueba, sin embargo, el algoritmo GA presentó un mejor desempeño consistentemente en todas las instancias de evaluación, encontrando en algunos casos hasta 10 portafolios óptimos en menos de 9 minutos.spa
dc.description.abstractThis article addresses the problem of project portfolio selection for the adjudication of public works audits through open merit competitions (CMA) supervised by the National Institute of Roads (INVIAS) in Colombia. In this modality, each contestant presents a unique portfolio of historical projects to quantify their experience as a controller. As an alternative to using Excel spreadsheets with limited exhaustive enumeration procedures, a meta-optimized genetic algorithm (GA) and a meta-optimized probabilistic adaptive greedy search procedure (GRASP) were evaluated for a Company case study. with 207 experience contracts in the sector. Both metaheuristics were able to find optimal evaluation scores for different test instances, however, the GA algorithm presented a consistently better performance in all evaluation instances, finding in some cases up to 10 optimal portfolios in less than 9 minutes.eng
dc.format.extent18 p.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/spa
dc.sourcehttps://revistas.eia.edu.co/index.php/reveia/article/view/1399/1349spa
dc.titleSelección óptima del portafolio de proyectos utilizando metaheurísticas de población y trayectoria meta-optimizadasspa
dc.title.alternativeOptimal Project Portfolio Selection Using Meta-Optimized Population and Trajectory-Based Metaheuristicseng
dc.typeArtículo de revistaspa
dc.description.notesRecibido: 03-01-2020Aceptado: 18-06-2020 Disponible online: 15-11-2020spa
dc.description.notesPublicación científica semestral Universidad EIA, Envigado, Colombiaspa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.contributor.researchgroupCentro de Investigaciones en Manufactura y Servicios - CIMSERspa
dc.identifier.doidoi.org/10.24050/reia.v17i34.1399
dc.identifier.urlhttps://revistas.eia.edu.co/index.php/reveia/article/view/1399/1349
dc.publisher.placeColombiaspa
dc.relation.citationeditionAño XVII, Volumen 17, Edición N.34, Julio-Diciembre de 2020spa
dc.relation.citationissue34spa
dc.relation.citationvolume17spa
dc.relation.indexedN/Aspa
dc.relation.ispartofjournalRevista EIAspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.creativecommonsAtribución 4.0 Internacional (CC BY 4.0)spa
dc.subject.armarcProyectos de construcciónspa
dc.subject.armarcConstruction projectseng
dc.subject.armarcAlgoritmos heurísticosspa
dc.subject.armarcHeuristic algorithmseng
dc.subject.armarcAlgoritmosspa
dc.subject.armarcAlgorithmseng
dc.subject.proposalAlgoritmo genéticospa
dc.subject.proposalGRASPspa
dc.subject.proposalMeta-optimizaciónspa
dc.subject.proposalSelección de portafolio de proyectosspa
dc.subject.proposalGenetic algorithmseng
dc.subject.proposalMeta-optimizationeng
dc.subject.proposalProject portfolio selectioneng
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa


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