A Generalized Golden Rule Representative Value for Multiple-Criteria Decision Analysis
Date
2021
Authors
Liu, Z.
Xiao, F.
Lin, C.T.
Kang, B.H.
Cao, Z.
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Journal article
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IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021; 51(5):3193-3204
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Abstract
Multicriteria decision analysis evaluates multiple conflicting criteria in decision making, but conflicting criteria are typical in evaluating options. As the existing ordering operations involved in multicriteria decision making cannot easily be implemented with intervals, we assume that scalar representative values with intervals can effectively avoid this issue. To deal with interval-valued criteria, we propose a generalized golden rule representative value approach, which involves the sigmoid function of backpropagation neural networks to tune parameters. Our approach considers the uncertainties and side effects of the interval variables to improve individual scalar representative values. Based on numerical examples, we address the effectiveness of the proposed approach, and we provide a specific application concerning multicriteria decision making with interval criteria satisfaction.
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Link to a related website: https://unpaywall.org/10.1109/TSMC.2019.2919243, Open Access via Unpaywall
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Copyright 2021 IEEE