A contextual Choquet integral-based preference learning model considering both criteria interactions and the compromise effects of decision-makers

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2023-03-01
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en
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EXPERT SYSTEMS WITH APPLICATIONS, Volume 213
Abstract
Preference learning has been widely employed to predict decision-makers’ preferences from historical information. This study develops a preference learning model for multiple criteria decision analysis where the decision-maker is supposed to be bounded rational and criteria are not completely independent of each other. The contextual Choquet integral is used as the aggregation function to address criteria interactions. The robust-ordinal-regression (ROR) technique is then applied to learn the preferences of decision-makers from the given preference data and provide robust decision recommendations. The proposed approach is illustrated by a numerical study concerning sustainable product evaluation.
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Keywords
Multiple criteria analysis, Preference learning, Compromise effect, Interactive criteria, Robust ordinal regression
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Citation
Liao, Z, Liao, H & Zhang, X 2023, ' A contextual Choquet integral-based preference learning model considering both criteria interactions and the compromise effects of decision-makers ', EXPERT SYSTEMS WITH APPLICATIONS, vol. 213, 118977 . https://doi.org/10.1016/j.eswa.2022.118977