Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/315082 
Year of Publication: 
2024
Citation: 
[Journal:] 4OR [ISSN:] 1614-2411 [Volume:] 22 [Issue:] 3 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2024 [Pages:] 313-349
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
This article elaborates on the connection between multiple criteria decision aiding (MCDA) and preference learning (PL), two research fields with different roots and developed in different communities. It complements the first part of the paper, in which we started with a review of MCDA. In this part, a similar review will be given for PL, followed by a systematic comparison of both methodologies, as well as an overview of existing work on combining PL and MCDA. Our main goal is to stimulate further research at the junction of these two methodologies.
Subjects: 
Preference learning
Preference modelling
Multiple criteria decision aiding
Multiple criteria decision making
Machine learning
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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