A Generic Framework to Include Belief Functions in Preference Handling for Multi-criteria Decision

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10369)

Abstract

Modelling the preferences of a decision maker about multi-criteria 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.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Sorbonne Université, UMR CNRS 7253 Heudiasyc, Université de Technologie de Compiègne CS 60319Compiègne CedexFrance

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