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

Multiple criteria sorting models and methods. Part II: theoretical results and general issues 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png 4OR Springer Journals

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

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References (71)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
ISSN
1619-4500
eISSN
1614-2411
DOI
10.1007/s10288-022-00531-3
Publisher site
See Article on Publisher Site

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.

Journal

4OR – Springer Journals

Published: Jun 1, 2023

Keywords: Multiple criteria decision making; Multiple criteria sorting; Monotone classification; Preference learning; 91B06; 90B50

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