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Soft Computing

, Volume 23, Issue 21, pp 10977–10982 | Cite as

Uncertain random simulation algorithm with application to bottleneck assignment problem

  • Sibo DingEmail author
  • Xiao-Jun Zeng
  • Huimin Zhang
Methodologies and Application
  • 84 Downloads

Abstract

Uncertain random simulation plays an important role in solving uncertain random optimization problems that include random variables and uncertain variables. In this paper, an uncertain random simulation is proposed and developed to obtain the chance distribution, \(\alpha \)-pessimistic value and \(\alpha \)-optimistic value. Further, an \(\alpha \)-optimal model for the uncertain random bottleneck assignment problem under the Hurwicz criterion is presented. Finally, a numerical example is given to illustrate how to use the proposed simulation algorithm to solve an uncertain random bottleneck assignment problem.

Keywords

\(\alpha \)-Pessimistic value \(\alpha \)-Optimistic value Uncertain random variable Assignment problem 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. U1404701), the Scholarship Program of China Scholarship Council (Grant No. 201509895007), the Scientific Research Foundation of the Henan University of Technology (Grant No. 2017RCJH11) and the Innovation Team Project of Philosophy and Social Sciences in Higher Education Institutions of Henan Province (Grant no. 2019-CXTD-04). We are grateful to anonymous reviewers for their thoughtful comments, which help considerably to improve the presentation of this work.

Compliance with ethical standard

Conflict of Interest

The authors declare that they have no conflict of interest.

Human and animal rights

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

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of ManagementHenan University of TechnologyZhengzhouChina
  2. 2.School of Computer ScienceUniversity of ManchesterManchesterUK

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