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dc.contributor.authorRivera Zarate, Gilberto
dc.date.accessioned2021-11-25T17:02:24Z
dc.date.available2021-11-25T17:02:24Z
dc.date.issued2021-08-27es_MX
dc.identifier.urihttp://cathi.uacj.mx/20.500.11961/19266
dc.description.abstractThis paper introduces an interactive approach to support multi-criteria decision analysis of project portfolios. In high-scale strategic decision domains, scientific studies suggest that the Decision Maker (DM) can find help by using many-objective optimisation methods, which are supposed to provide values in the decision variables that generate high-quality solutions. Even so, DMs usually wish to explore the possibility of reaching some levels of benefits in some objectives. Consequently, they should repeatedly run the optimisation method. However, this approach cannot perform well – in an interactive way – for large instances under the presence of many objective functions. We present a mathematical model that is based on compromise programming and fuzzy outranking to aid DMs in analysing multi-criteria project portfolios on the fly. This approach allows relaxing the problem of rapidly optimising portfolios while preserving the beneficial properties of the DM’s preferences expressed by outranking relations. Our model supports the decision analysis on two instance benchmarks: for the first one, a better compromise solution was generated 84% of the runs; for the second one, this ranged from 93% to 97%. Our model was also applied to a real-world problem involving social projects, obtaining satisfactory results.es_MX
dc.description.urihttps://www.sciencedirect.com/science/article/abs/pii/S0020025521009014es_MX
dc.language.isoen_USes_MX
dc.relation.ispartofProducto de investigación IITes_MX
dc.relation.ispartofInstituto de Ingeniería y Tecnologíaes_MX
dc.subjectPortfolio Optimizationes_MX
dc.subjectPreference Incorporationes_MX
dc.subjectFuzzy Outrankinges_MX
dc.subject.otherinfo:eu-repo/classification/cti/7es_MX
dc.titleOnline multi-criteria portfolio analysis through compromise programming models built on the underlying principles of fuzzy outrankinges_MX
dc.typeArtículoes_MX
dcterms.thumbnailhttp://ri.uacj.mx/vufind/thumbnails/rupiiit.pnges_MX
dcrupi.institutoInstituto de Ingeniería y Tecnologíaes_MX
dcrupi.cosechableSies_MX
dcrupi.volumen580es_MX
dcrupi.nopagina734-755es_MX
dc.identifier.doi10.1016/j.ins.2021.08.087es_MX
dc.contributor.coauthorSánchez Solís, Julia Patricia
dc.contributor.coauthorFlorencia, Rogelio
dc.journal.titleInformation Scienceses_MX
dc.contributor.coauthorexternoPorras, Gibran
dc.contributor.coauthorexternoGuerrero, Mario
dcrupi.pronacesNingunoes_MX


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