Preference Elicitation for a Ranking Method based on Multiple Reference Profiles
Résumé
Multiple Criteria Decision Aid (MCDA) metholodolgies support decision makers (DM) facing decisions involving conflicting objectives. DM's preferences should be captured to provide meaningful recommendations. Preference elicitation aims at incorporating DM's preferences in decision models. We propose preference elicitation tool for a new ranking model based on reference points (S-RMP). Our methodology infers an S-RMP model from a list of pairwise comparisons provided by the DM. the inference algorithm makes use of a Mixed Integer mathematical programming formulation. We prove the applicability by performing extensive numerical experiments on datasets whose size corresponding to real-world problem.
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