A metaheuristic for inferring a ranking model based on multiple reference profiles - Equipe DECIDE, from data to decision Access content directly
Journal Articles Annals of Mathematics and Artificial Intelligence Year : 2024

A metaheuristic for inferring a ranking model based on multiple reference profiles

Abstract

In the context of Multiple Criteria Decision Aiding, decision makers often face problems with multiple conflicting criteria that justify the use of preference models to help advancing towards a decision. In order to determine the parameters of these preference models, preference elicitation makes use of preference learning algorithms, usually taking as input holistic judgments expressed by the decision maker. Tools to achieve this goal in the context of a ranking model based on multiple reference profiles are usually based on mixed-integer linear programming or constraint programming. However, they are usually unable to handle realistic problems involving many criteria and a large amount of input information. We propose here an evolutionary metaheuristic in order to address this issue. Extensive experiments illustrate its ability to handle problem instances that previous proposals cannot.
Fichier principal
Vignette du fichier
A_metaheuristic_for_inferring_a_ranking_model_based_on_multiple_reference_profiles___AMAI.pdf (509.43 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04017642 , version 1 (07-03-2023)
hal-04017642 , version 2 (09-02-2024)

Identifiers

Cite

Arwa Khannoussi, Alexandru-Liviu Olteanu, Patrick Meyer, Bastien Pasdeloup. A metaheuristic for inferring a ranking model based on multiple reference profiles. Annals of Mathematics and Artificial Intelligence, 2024, ⟨10.1007/s10472-024-09926-w⟩. ⟨hal-04017642v2⟩
98 View
85 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More