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Optimal Grouping of Heterogeneous Components in Series and Parallel Systems Under Archimedean Copula Dependence

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Abstract

This paper considers series and parallel systems comprising n components drawn from a heterogeneous population consisting of m different subpopulations. The components within each subpopulation are assumed to be dependent, while the subpopulations are independent of each other. The authors also assume that the subpopulations have different Archimedean copulas for their dependence. Under this setup, the authors discuss the series and parallel systems reliability for three different cases, respectively. The authors use the theory of stochastic orders and majorization to establish the main results, and finally present some numerical examples to illustrate all the results established here.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, Anhui Normal University, Wuhu, 241000, China

    Longxiang Fang

  2. Department of Statistics, Fudan University, Shanghai, 200433, China

    Xinsheng Zhang

  3. Department of Mathematics and Statistics, Anhui Normal University, Wuhu, 241000, China

    Qing Jin

Authors
  1. Longxiang Fang
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  2. Xinsheng Zhang
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  3. Qing Jin
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Corresponding author

Correspondence to Longxiang Fang.

Additional information

This research was supported by the National Natural Science Foundation of China under Grant No. 11971116, the Anhui Provincial Natural Science Foundation under Grant No. 1808085MA03, and the PhD research startup foundation of Anhui Normal University under Grant No. 2014bsqdjj34.

This paper was recommended for publication by Editor ZHANG Xinyu.

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Fang, L., Zhang, X. & Jin, Q. Optimal Grouping of Heterogeneous Components in Series and Parallel Systems Under Archimedean Copula Dependence. J Syst Sci Complex 35, 1030–1051 (2022). https://doi.org/10.1007/s11424-021-0037-0

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  • DOI: https://doi.org/10.1007/s11424-021-0037-0

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