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Dynamic network reliability modeling under nonhomogeneous Poisson processes

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  • Zarezadeh, S.
  • Asadi, M.
  • Balakrishnan, N.

Abstract

In this paper, we consider a two-state (up and down) network consisting of n links. We study the D-spectrum based dynamic reliability of the network under the assumption that the links are subject to failure according to a nonhomogeneous Poisson process. Several mixture representations are provided for the reliability function of residual lifetime of used networks, under different conditions on the status of the network or its links. These representations enable us to explore the residual reliability of operating networks in terms of the reliability functions of residual lifetimes of upper record values. The distribution function of inactivity time of a network is examined under the condition that the network has failed by inspection time t. Stochastic ordering properties of the residual lifetimes of networks under conditional D-spectra are investigated. Several examples and graphs are also provided to illustrate the established results.

Suggested Citation

  • Zarezadeh, S. & Asadi, M. & Balakrishnan, N., 2014. "Dynamic network reliability modeling under nonhomogeneous Poisson processes," European Journal of Operational Research, Elsevier, vol. 232(3), pages 561-571.
    • Handle: RePEc:eee:ejores:v:232:y:2014:i:3:p:561-571
    DOI: 10.1016/j.ejor.2013.07.037
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    References listed on IDEAS

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    1. Navarro, Jorge & Rychlik, Tomasz, 2010. "Comparisons and bounds for expected lifetimes of reliability systems," European Journal of Operational Research, Elsevier, vol. 207(1), pages 309-317, November.
    2. Eryilmaz, Serkan, 2012. "On the mean residual life of a k-out-of-n:G system with a single cold standby component," European Journal of Operational Research, Elsevier, vol. 222(2), pages 273-277.
    3. Levitin, G. & Gertsbakh, I. & Shpungin, Y., 2011. "Evaluating the damage associated with intentional network disintegration," Reliability Engineering and System Safety, Elsevier, vol. 96(4), pages 433-439.
    4. Khaledi, Baha-Eldin & Shaked, Moshe, 2010. "Stochastic comparisons of multivariate mixtures," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2486-2498, November.
    5. Avinash Agrawal & Richard E. Barlow, 1984. "A Survey of Network Reliability and Domination Theory," Operations Research, INFORMS, vol. 32(3), pages 478-492, June.
    6. Navarro, Jorge & Rychlik, Tomasz, 2007. "Reliability and expectation bounds for coherent systems with exchangeable components," Journal of Multivariate Analysis, Elsevier, vol. 98(1), pages 102-113, January.
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    Citations

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    Cited by:

    1. Alkaff, Abdullah, 2021. "Discrete time dynamic reliability modeling for systems with multistate components," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Zarezadeh, S. & Mohammadi, L. & Balakrishnan, N., 2018. "On the joint signature of several coherent systems with some shared components," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1092-1100.
    3. Cha, Ji Hwan, 2019. "Poisson Lindley process and its main properties," Statistics & Probability Letters, Elsevier, vol. 152(C), pages 74-81.
    4. Somayeh Zarezadeh & Somayeh Ashrafi & Majid Asadi, 2018. "Network Reliability Modeling Based on a Geometric Counting Process," Mathematics, MDPI, vol. 6(10), pages 1-17, October.
    5. Ma, Chengye & Du, Yongjun & Zhang, Yuchun & Cai, Zhiqiang, 2022. "Marginal and joint failure importance for K-terminal network edges under counting process," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    6. Serkan Eryilmaz & G. Tutuncu, 2015. "Relative behavior of a coherent system with respect to another coherent system," Statistical Papers, Springer, vol. 56(2), pages 519-529, May.

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