Artículo
Inferring efficient weights from pairwise comparison matrices
Autor/es | Blanquero Bravo, Rafael
Carrizosa Priego, Emilio José Conde Sánchez, Eduardo |
Departamento | Universidad de Sevilla. Departamento de Estadística e Investigación Operativa |
Fecha de publicación | 2006-10 |
Fecha de depósito | 2016-10-20 |
Publicado en |
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Resumen | Several 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 ... Several 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. |
Agencias financiadoras | Ministerio de Ciencia y Tecnología (MCYT). España European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER) |
Identificador del proyecto | BFM2002-04525-C02-02
BFM2002-11282-E |
Cita | Blanquero 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. |
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