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Averaging aggregation under uncertainty and bipolar preference environments

  • Soft computing in decision making and in modeling in economics
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Abstract

Uncertainty in information provides the possibility of having and applying preferences, and therefore, it necessitates the study of preferences-involved aggregation theory and techniques under uncertainty information environments. Hence, this paper discusses several rules-based decision-making methods in uncertain decision scenarios with or without fusion processes. Some special averaging aggregation methods and transformations for basic uncertain information vector are proposed. [0, 1]-valued, [\(-1\), 1]-valued, and vector-valued bipolar preferences with some of their relations are discussed. The discussions and analyses of aggregation mainly revolve around Sugeno integral. Finally, multiple aggregation schemes with vector-valued preferences with numerical examples are proposed, and some few related comparisons are provided.

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Acknowledgements

The authors would like to thank the Editor-in-Chief, the Associate Editor, and the anonymous referees for their prompt, thorough, and insightful comments on this paper.

Funding

This work is partly supported by the National Natural Science Foundation of China (Grant Nos. 72171182 and 71801175), grant APVV-18-0052, VEGA 1/0006/19, and the grant Palacky University Olomouc IGAPrF2021.

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Correspondence to Zhen-Song Chen.

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Jin, L., Yager, R.R., Chen, ZS. et al. Averaging aggregation under uncertainty and bipolar preference environments. Soft Comput 27, 8153–8159 (2023). https://doi.org/10.1007/s00500-023-08152-6

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