Multicriteria Decision Making Based on Qualitative Assessments and Relational Belief

Amel Ennaceur (1) , Zied Elouedi (1) , Eric Lefevre (2)

1 LARODEC - Laboratoire de Recherche Opérationnelle de Décision et de Contrôle de Processus
2 LGI2A - Laboratoire de Génie Informatique et d'Automatique de l'Artois

This paper investigates a multi-criteria decision making method in an uncertain environment, where the uncertainty is represented using the belief function framework. Indeed, we suggest a novel methodology that tackles the challenge of introducing uncertainty in both the criterion and the alternative levels. On the one hand and in order to judge the criteria weights, our proposed approach suggests to use preference relations to elicitate the decision maker assessments. Therefore, the Analytic Hierarchy Process with qualitative belief function framework is adopted to get adequate numeric representation. On the other hand, our model assumes that the evaluation of each alternative with respect to each criterion may be imperfect and it can be represented by a basic belief assignment. That is why, a new aggregation procedure that is able to rank alternatives is introduced.

Domaines: Intelligence artificielle [cs.AI]

Amel Ennaceur, Zied Elouedi, Eric Lefevre. Multicriteria Decision Making Based on Qualitative Assessments and Relational Belief. Congress of the Italian Association for Artificial Intelligence, AI*IA'2013, Dec 2013, Turin, Italy. pp.48-59, ⟨10.1007/978-3-319-03524-6_5⟩. ⟨hal-03649717⟩