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dc.contributor.authorGómez, Claudia
dc.date.accessioned2018-12-03T19:51:00Z
dc.date.available2018-12-03T19:51:00Z
dc.date.issued2018-06-17
dc.identifier.isbn978-3-319-56871-3es_MX
dc.identifier.isbn978-3-319-56870-6es_MX
dc.identifier.urihttp://cathi.uacj.mx/20.500.11961/4366
dc.description.abstractThe Project Portfolio Problem (PPP) has been solved through different approaches. The success of some of them is related to a proper application of the decision-maker’s preferences, and a correct identification of organization’s resource practices and conditions. However, there are still a small number of classes of PPP that have been solved using these approaches, and there is also a need for increasing them. Due to this situation, the present research develops a strategy, based on ant colony optimization that incorporates the decision-maker’s preferences into the solution of a case of PPP under conditions of synergy, cannibalization, redundancy, and with interactions between projects. The algorithm was experimentally tested, and the results show a good performance of it over a random set of instances.es_MX
dc.description.urihttps://link.springer.com/chapter/10.1007/978-3-319-56871-3_13es_MX
dc.language.isoen_USes_MX
dc.publisherSpringeres_MX
dc.relation.ispartofProducto de investigación IITes_MX
dc.relation.ispartofInstituto de Ingeniería y Tecnologíaes_MX
dc.subjectAnt colony optimization algorithmes_MX
dc.subjectMulti-objective project portfolio selectiones_MX
dc.subjectOutranking modeles_MX
dc.subject.otherinfo:eu-repo/classification/cti/1es_MX
dc.titleInterdependent Projects Selection with Preference Incorporationes_MX
dc.typeCapítulo de libroes_MX
dcterms.thumbnailhttp://ri.uacj.mx/vufind/thumbnails/rupiiit.pnges_MX
dcrupi.institutoInstituto de Ingeniería y Tecnologíaes_MX
dcrupi.cosechableSies_MX
dcrupi.subtipoInvestigaciónes_MX
dcrupi.nopagina253-271es_MX
dcrupi.alcanceInternacionales_MX
dcrupi.paisSwitzerlandes_MX
dc.identifier.doidoi.org/10.1007/978-3-319-56871-3_13es_MX
dc.contributor.coauthorRivera-Zárate, Gilberto
dcrupi.estadoChames_MX
dc.lgacOPTIMIZACIÓN INTELIGENTEes_MX
dc.cuerpoacademicoInteligencia Artificial Aplicadaes_MX
dcrupi.titulolibroNew Perspectives on Applied Industrial Tools and Techniqueses_MX


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