Abstract
This paper characterizes the minimum risk path selection problem in an uncertain network. Assuming the accidental losses are the uncertain variables, we first present three types of uncertain risk indexes. After that, some uncertain risk programming models are built based on the proposed risk indexes. In order to obtain the minimum risk path, we convert these uncertain programming models to their corresponding deterministic forms by the operational law of uncertain variables. At last, a numerical example is given to demonstrate the models.
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This work is supported by the National Natural Science Foundation of China Grant Nos. 61873108, 61703438 and 11626234.
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Li, S., Peng, J. & Zhang, B. The risk path selection problem in uncertain network. Soft Comput 24, 6375–6383 (2020). https://doi.org/10.1007/s00500-019-04132-x
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DOI: https://doi.org/10.1007/s00500-019-04132-x