Abstract
Uncertainty theory, founded in 2007, has become a branch of mathematics to model uncertainty rather than randomness. As an indispensable part of uncertainty theory, uncertain graph and uncertain network optimization has received the wide attention of many scholars. Naturally, a series of original research achievements have been obtained on uncertain graph and uncertain network optimization. This paper aims to present a state-of-the-art review on the recent advance in uncertain graph and uncertain network optimization. Furthermore, it hopes to predict the possible future research directions. Based on Web of Science database, this paper retrieves 144 related papers from 2011 to 2021 to analyze the features of published articles. More precisely, we analyze the annual number of publications, key topics and sub-fields, journals, and most-cited articles. In addition, the main results and models for uncertain graph and uncertain network optimization are summarized. Furthermore, the limitations of existing literature and the possible development trend are discussed.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (Nos. 61873108, 61703438, 72102171 and 72071092), the National Statistical Science Research Project of China (No. 2022LY058), the Hubei Provincial Natural Science Foundation of China (No. 2022CFB415) and the Scientific Research Project of Education Department of Hubei Provincial of China (No. Q20203001).
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Peng, J., Zhang, B., Chen, L. et al. A survey on uncertain graph and uncertain network optimization. Fuzzy Optim Decis Making 23, 129–153 (2024). https://doi.org/10.1007/s10700-023-09413-7
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DOI: https://doi.org/10.1007/s10700-023-09413-7