Determination of weights of interacting criteria from a reference set

By Jean-Luc Marichal, Marc Roubens. European Journal of Operational Research, 2000

300 citations recorded by the source corpus.

Abstract In this paper, we present a model allowing to determine the weights related to interacting criteria. This is done on the basis of the knowledge of a partial ranking over a reference set of alternatives (prototypes), a partial ranking over the set of criteria, and a partial ranking over the set of interactions between pairs of criteria.

Subfields: Artificial Intelligence, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ae456945beaa2ebc21b36a8ffa298f74c6b42f79

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Behavioral analysis of aggregation in multicriteria decision aid (2000, methodology): “This corresponds to the inverse problem of identifying the weights from parametric specifications on criteria, see [14].”
A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid (2008, methodology): “This method proposed by Marichal and Roubens (2000) consists in maximizing the difference in overall scores among alternatives: if the decision maker prefers (in the strict sense) x to x′, then this should be reflected in the model by two sufficiently different outputs.”
Combining analytical hierarchy process and Choquet integral within non-additive robust ordinal regression ☆ (2016, background): “preference information provided by the DM ([2, 46]; for an extensive review on the topic see also [33] and [35]).”
Axiomatic characterizations of probabilistic and cardinal-probabilistic interaction indices (2006, methodology): “In this context, it is used to appraise the overall interaction among criteria [8, 9, 15, 20, 21, 22, 24], thereby giving more insight into the decision problem.”
A review of methods for capacity identification in Choquet integral based multi-attribute utility theory: Applications of the Kappalab R package (2008, methodology): “This approach, which is due to Meyer and Roubens [38], can be seen as a generalization of the least squares methods described in Subsection 4.1.”