Modelling the preferences of a decision maker about multicriteria alternatives usually starts by collecting preference information, then used to fit a model issued from a set of hypothesis (weighted average, CP-net). This can lead to inconsistencies, due to inaccurate information provided by the decision maker or to a poor choice of hypothesis set. We propose to quantify and resolve such inconsistencies, by allowing the decision maker to express her/his certainty about the provided preferential information in the form of belief functions.
CITATION STYLE
Destercke, S. (2017). A generic framework to include belief functions in preference handling for multi-criteria decision. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10369 LNAI, pp. 179–189). Springer Verlag. https://doi.org/10.1007/978-3-319-61581-3_17
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