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dc.contributor.authorSlowinski, Roman
dc.contributor.authorMousseau, Vincent
HAL ID: 4625
dc.contributor.authorGreco, Salvatore
dc.date.accessioned2010-03-16T09:09:45Z
dc.date.available2010-03-16T09:09:45Z
dc.date.issued2008
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/3702
dc.language.isoenen
dc.subjectMultiple criteria rankingen
dc.subjectOrdinal regression approachen
dc.subjectAdditive value functionen
dc.subject.ddc003en
dc.titleOrdinal regression revisited: multiple criteria ranking using a set of additive value functionsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe present a new method, called UTAGMS, for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. The preference information provided by the decision maker is a set of pairwise comparisons on a subset of alternatives AR subset of or equal to A, called reference alternatives. The preference model built via ordinal regression is the set of all additive value functions compatible with the preference information. Using this model, one can define two relations in the set A: the necessary weak preference relation which holds for any two alternatives a, b from set A if and only if for all compatible value functions a is preferred to b, and the possible weak preference relation which holds for this pair if and only if for at least one compatible value function a is preferred to b. These relations establish a necessary and a possible ranking of alternatives from A, being, respectively, a partial preorder and a strongly complete relation. The UTAGMS method is intended to be used interactively, with an increasing subset AR and a progressive statement of pairwise comparisons. When no preference information is provided, the necessary weak preference relation is a weak dominance relation, and the possible weak preference relation is a complete relation. Every new pairwise comparison of reference alternatives, for which the dominance relation does not hold, is enriching the necessary relation and it is impoverishing the possible relation, so that they converge with the growth of the preference information. Distinguishing necessary and possible consequences of preference information on the complete set of actions, UTAGMS answers questions of robustness analysis. Moreover, the method can support the decision maker when his/her preference statements cannot be represented in terms of an additive value function. The method is illustrated by an example solved using the UTAGMS software. Some extensions of the method are also presented.en
dc.relation.isversionofjnlnameEuropean Journal of Operational Research
dc.relation.isversionofjnlvol191en
dc.relation.isversionofjnlissue2en
dc.relation.isversionofjnldate2008-12
dc.relation.isversionofjnlpages416-436en
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/j.ejor.2007.08.013en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelRecherche opérationnelleen


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