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dc.creatorBlanquero Bravo, Rafaeles
dc.creatorCarrizosa Priego, Emilio Josées
dc.creatorConde Sánchez, Eduardoes
dc.date.accessioned2016-10-20T12:19:23Z
dc.date.available2016-10-20T12:19:23Z
dc.date.issued2006-10
dc.identifier.citationBlanquero Bravo, R., Carrizosa Priego, E.J. y Conde Sánchez, E. (2006). Inferring efficient weights from pairwise comparison matrices. Mathematical Methods of Operations Research, 64 (2), 271-284.
dc.identifier.issn1432-2994es
dc.identifier.issn1432-5217es
dc.identifier.urihttp://hdl.handle.net/11441/47872
dc.description.abstractSeveral multi-criteria-decision-making methodologies assume the existence of weights associated with the different criteria, reflecting their relative importance.One of the most popular ways to infer such weights is the analytic hierarchy process, which constructs first a matrix of pairwise comparisons, from which weights are derived following one out of many existing procedures, such as the eigenvector method or the least (logarithmic) squares. Since different procedures yield different results (weights) we pose the problem of describing the set of weights obtained by “sensible” methods: those which are efficient for the (vector-) optimization problem of simultaneous minimization of discrepancies. A characterization of the set of efficient solutions is given, which enables us to assert that the least-logarithmic-squares solution is always efficient, whereas the (widely used) eigenvector solution is not, in some cases, efficient, thus its use in practice may be questionable.es
dc.description.sponsorshipMinisterio de Ciencia y Tecnologíaes
dc.description.sponsorshipFondo Europeo de Desarrollo Regionales
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherSpringeres
dc.relation.ispartofMathematical Methods of Operations Research, 64 (2), 271-284.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectDecision analysises
dc.subjectMulti-objectivees
dc.subjectOptimizationes
dc.subjectFractional programminges
dc.titleInferring efficient weights from pairwise comparison matriceses
dc.typeinfo:eu-repo/semantics/articlees
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Estadística e Investigación Operativaes
dc.relation.projectIDBFM2002-04525-C02-02es
dc.relation.projectIDBFM2002-11282-Ees
dc.relation.publisherversionhttp://download.springer.com/static/pdf/467/art%253A10.1007%252Fs00186-006-0077-1.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00186-006-0077-1&token2=exp=1476967042~acl=%2Fstatic%2Fpdf%2F467%2Fart%25253A10.1007%25252Fs00186-006-0077-1.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007%252Fs00186-006-0077-1*~hmac=7da6259e044439479c86f479200fb94ae1c1c7c9038fa02a0e710db82f773933es
dc.identifier.doi10.1007/s00186-006-0077-1es
dc.contributor.groupUniversidad de Sevilla. FQM329: Optimizaciónes
dc.contributor.groupUniversidad de Sevilla. FQM331: Métodos y Modelos de la Estadística y la Investigación Operativaes
idus.format.extent13 p.es
dc.journaltitleMathematical Methods of Operations Researches
dc.publication.volumen64es
dc.publication.issue2es
dc.publication.initialPage271es
dc.publication.endPage284es
dc.identifier.idushttps://idus.us.es/xmlui/handle/11441/47872
dc.contributor.funderMinisterio de Ciencia y Tecnología (MCYT). España
dc.contributor.funderEuropean Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER)

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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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