2010
DOI: 10.1016/j.ejor.2010.03.009
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ACUTA: A novel method for eliciting additive value functions on the basis of holistic preference statements

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Cited by 79 publications
(33 citation statements)
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“…To carry out the decision-making process for the evaluation, we resort to a multiple criteria decision aid (MCDA) technique named ACUTA (Analytic Centre UTilité Additive) based on the computation of the analytic centre of a polyhedron for the selection of additive value functions that are compatible with holistic assessments of the preferences in the criteria (Bous, Fortemps, Glineur, & Pirlot 2010). Being central by definition and uniquely defined, the analytic centre benefits from theoretical advantages over the notion of centrality used in other meta-UTA methods.…”
Section: Assessment Methodologymentioning
confidence: 99%
See 1 more Smart Citation
“…To carry out the decision-making process for the evaluation, we resort to a multiple criteria decision aid (MCDA) technique named ACUTA (Analytic Centre UTilité Additive) based on the computation of the analytic centre of a polyhedron for the selection of additive value functions that are compatible with holistic assessments of the preferences in the criteria (Bous, Fortemps, Glineur, & Pirlot 2010). Being central by definition and uniquely defined, the analytic centre benefits from theoretical advantages over the notion of centrality used in other meta-UTA methods.…”
Section: Assessment Methodologymentioning
confidence: 99%
“…The theoretical framework around this concept lies at the heart of interiorpoint methods for solving linear programming optimisation problems. In ACUTA, it is suggested to compute a unique, well-defined and central solution for aggregation-disaggregation methods based on additive piecewise linear value function models (Bous, Fortemps, Glineur, & Pirlot 2010).…”
Section: Analytic Centermentioning
confidence: 99%
“…Obviously, it is possible to conduct optimization of these differences taking advantage of other rules that have been proposed in the literature (see, e.g., Bous et al 2010;Despotis et al 1990). However, we have decided to apply a maximin rule, and search for such a function in the feasible space, which maximizes the smallest distance to any introduced constraint.…”
Section: Proposition 34 Considering Two Subsets Of Dmsmentioning
confidence: 99%
“…Assuming an additive value function, the statement that alternative x (1) is preferred to alternative x (2) can be represented by the condition (see, e.g., [11,31]):…”
Section: Representation Of Incomplete Informationmentioning
confidence: 99%
“…This is an approach used for inferring parameters of multicriteria aggregation approaches (e.g., [2,11,21]). Let A k denote a coefficient matrix and let b k denote a righthand side vector such that (w,…”
Section: Central Parameters Approachmentioning
confidence: 99%