Multiple criteria sorting models and methods—Part I: survey of the literature
Khaled Belahcène,
Vincent Mousseau,
Wassila Ouerdane,
Marc Pirlot () and
Olivier Sobrie
Additional contact information
Khaled Belahcène: Heudiasyc, Université de Technologie de Compiègne
Vincent Mousseau: MICS, CentraleSupélec, Université Paris-Saclay
Wassila Ouerdane: MICS, CentraleSupélec, Université Paris-Saclay
Marc Pirlot: MATHRO, Faculté Polytechnique, Université de Mons
Olivier Sobrie: MATHRO, Faculté Polytechnique, Université de Mons
4OR, 2023, vol. 21, issue 1, No 1, 46 pages
Abstract:
Abstract Multiple criteria sorting methods assign objects into ordered categories while objects are characterized by a vector of n attributes values. Categories are ordered, and the assignment of the object is monotonic w.r.t. to some underlying order on the attributes scales (criteria). Our goal is to offer a survey of the literature on multiple criteria sorting methods, since the origins, in the 1980s, focusing on the underlying models. Our proposal is organized into two parts. In Part I, we start by recalling two main models, one based on additive value functions (UTADIS) and the other on an outranking relation (Electre Tri). Then we draw a (structured) picture of multiple criteria sorting models and the methods designed for eliciting their parameters or learning them based on assignment examples. In Part II (to appear in a forthcoming issue of this journal), we attempt to provide a theoretical view of the field and position some existing models within it. We then discuss issues related to imperfect or insufficient information.
Keywords: Multiple criteria decision making; Multiple criteria sorting; Monotone classification; Preference learning; 91B06; 90B50 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)
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DOI: 10.1007/s10288-022-00530-4
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