Multiple criteria sorting models and methods. Part II: theoretical results and general issues

Khaled Belahcène, Vincent Mousseau, Wassila Ouerdane, Marc Pirlot () and Olivier Sobrie
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Khaled Belahcène: Université de Technologie de Compiègne
Vincent Mousseau: Université Paris-Saclay
Wassila Ouerdane: Université Paris-Saclay
Marc Pirlot: Université de Mons
Olivier Sobrie: Université de Mons

4OR, 2023, vol. 21, issue 2, No 1, 204 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). We drew a landscape of these methods in Part I “Survey of the literature” (published in a previous issue of the present journal) and we aim to provide a theoretical view of the field in this second part. We describe a general framework for MCS models and position some existing models in the picture. Issues related to imperfect or insufficient information are then discussed. We also address questions that arise in the final phase of a decision aiding process as, e.g., explaining a recommendation or suggesting efficient ways of improving an object assignment.

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 (2)

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DOI: 10.1007/s10288-022-00531-3

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