Abstract
This paper investigates a multi-criteria decision making met-hod 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.
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Ennaceur, A., Elouedi, Z., Lefevre, E. (2013). Multicriteria Decision Making Based on Qualitative Assessments and Relational Belief. In: Baldoni, M., Baroglio, C., Boella, G., Micalizio, R. (eds) AI*IA 2013: Advances in Artificial Intelligence. AI*IA 2013. Lecture Notes in Computer Science(), vol 8249. Springer, Cham. https://doi.org/10.1007/978-3-319-03524-6_5
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DOI: https://doi.org/10.1007/978-3-319-03524-6_5
Publisher Name: Springer, Cham
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