Uncertain random shortest path problem

  • Yuhong Sheng
  • Xuehui Mei


The shortest path is an important problem in network optimization theory. This paper considers the shortest path problem under the situation where weights of edges in a network include both uncertainty and randomness and focuses on the case that the weights of edges are expressed by uncertain random variables. Some optimization models based on chance theory are proposed in order to find the shortest path which fully reflects uncertain and random information. This paper proposes also an intelligent algorithm to calculate the shortest path for an uncertain random network. A numerical example is given to illustrate its effectiveness.


Shortest path problem Chance theory Uncertain random variable Uncertain random network 



This work was supported by National Natural Science Foundation of China (Grants No. 61563050), Joint Key Program of National Natural Science Foundation of China (Grants No. U1703262), Innovation Team Research Program of Universities in Xinjiang Uyghur Autonomous Region (Grants No. XJEDU2017 T001), and this work was granted by China Scholarship Council (Grants 201708 655050).

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Mathematical and System SciencesXinjiang UniversityÜrümqiChina

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