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A linear programming approach for learning non-monotonic additive value functions in multiple criteria decision aiding

Author
Ghaderi, M.; Ruiz, F.; Agell, N.
Type of activity
Journal article
Journal
European journal of operational research
Date of publication
2017-06-16
Volume
259
Number
3
First page
1073
Last page
1084
DOI
https://doi.org/10.1016/j.ejor.2016.11.038 Open in new window
Repository
https://www.researchgate.net/publication/310837599_A_Linear_Programming_Approach_for_Learning_Non-Monotonic_Additive_Value_Functions_in_Multiple_Criteria_Decision_Aiding Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0377221716309638 Open in new window
Abstract
A new framework for preference disaggregation in multiple criteria decision aiding is introduced. The proposed approach aims to infer non-monotonic additive preference models from a set of indirect pair wise comparisons. The preference model is presented as a set of marginal value functions and the discriminatory power of the inferred preference model is maximized against its complexity. To infer a value function that is compatible with the supplied preference information, the proposed methodolo...
Keywords
Decision analysis, Linear programming, Multiple criteria analysis, Non-monotonic value functions, Preference disaggregation
Group of research
GREC - Knowledge Engineering Research Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants