IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v237y2023i6p1031-1047.html
   My bibliography  Save this article

Redundancy allocation optimization for multi-state system with hierarchical performance requirements

Author

Listed:
  • Jing Li
  • Guodong Wang
  • Haofei Zhou
  • Honggen Chen

Abstract

Conventional redundancy allocation optimization model is usually measured by single performance. It meets difficulties in modeling the redundancy allocation optimization of multi-state system (MSS) with hierarchical performance requirements. This study proposes a generalized optimization model for MSS. This model concentrates on the redundancy allocation problem of the MSS with the inter-level dependent performances requirements. In the case of the minimum cost or maximum availability of the system, the aim of this model is to optimize system configuration, such as the economic numbers and versions for the multilevel heterogeneous components with known reliability and cost characteristics. Firstly, two algorithms to evaluate the system availability are introduced. A modified universal generation function (UGF) algorithm combining hierarchical operators is developed to evaluate the accurate availability for the system. Then the recursive algorithm (RA) is also used to obtain the lower and upper bounds of system availability. Secondly, compared with the traditional optimization model for the single level system, the proposed model for the hierarchical system has more decision variables which lead to difficult computation. Therefore, the genetic algorithm (GA) is applied to solve the redundancy allocation, especially the optimal numbers and versions of the different-level components simultaneously. Finally, a realistic power system verifies the correctness and validity of the suggested model. In conclusion, the results show that the above model tends to be more flexible and effective in the redundancy allocation optimization. Furthermore, this model helps the engineer in the reliability design optimization for the complex systems.

Suggested Citation

  • Jing Li & Guodong Wang & Haofei Zhou & Honggen Chen, 2023. "Redundancy allocation optimization for multi-state system with hierarchical performance requirements," Journal of Risk and Reliability, , vol. 237(6), pages 1031-1047, December.
    • Handle: RePEc:sae:risrel:v:237:y:2023:i:6:p:1031-1047
    DOI: 10.1177/1748006X221123974
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X221123974
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X221123974?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Bora Çekyay, 2021. "Reliability of mission-based k-out-of-n systems with exponential phase durations and component lifetimes," Journal of Risk and Reliability, , vol. 235(3), pages 446-457, June.
    2. Wang, Yong & Li, Lin & Huang, Shuhong & Chang, Qing, 2012. "Reliability and covariance estimation of weighted k-out-of-n multi-state systems," European Journal of Operational Research, Elsevier, vol. 221(1), pages 138-147.
    3. Zhang, Yongjin & Zhao, Ming & Zhang, Yanjun & Pan, Ruilin & Cai, Jing, 2020. "Dynamic and steady-state performance analysis for multi-state repairable reconfigurable manufacturing systems with buffers," European Journal of Operational Research, Elsevier, vol. 283(2), pages 491-510.
    4. Zhigang Tian & Ming Zuo & Richard Yam, 2009. "Multi-state systems and their performance evaluation," IISE Transactions, Taylor & Francis Journals, vol. 41(1), pages 32-44.
    5. Fábio Usberti & Christiano Lyra & Celso Cavellucci & José González, 2015. "Hierarchical multiple criteria optimization of maintenance activities on power distribution networks," Annals of Operations Research, Springer, vol. 224(1), pages 171-192, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Faghih-Roohi, Shahrzad & Xie, Min & Ng, Kien Ming & Yam, Richard C.M., 2014. "Dynamic availability assessment and optimal component design of multi-state weighted k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 57-62.
    2. Sheng, Yuhong & Ke, Hua, 2020. "Reliability evaluation of uncertain k-out-of-n systems with multiple states," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    3. Jørgen Vitting Andersen & Roy Cerqueti & Giulia Rotundo, 2017. "Rational expectations and stochastic systems," Documents de travail du Centre d'Economie de la Sorbonne 17060, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Oct 2019.
    4. Wang, Guanjun & Duan, Fengjun & Zhou, Yifan, 2018. "Reliability evaluation of multi-state series systems with performance sharing," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 58-63.
    5. Yonit Barron, 2018. "Group maintenance policies for an R-out-of-N system with phase-type distribution," Annals of Operations Research, Springer, vol. 261(1), pages 79-105, February.
    6. Jorgen Vitting Andersen & Roy Cerqueti & Jessica Riccioni, 2021. "Rational expectations as a tool for predicting failure of weighted k-out-of-n reliability systems," Papers 2112.10672, arXiv.org.
    7. Zhang, Hanxiao & Sun, Muxia & Li, Yan-Fu, 2022. "Reliability–redundancy allocation problem in multi-state flow network: Minimal cut-based approximation scheme," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    8. Serkan Eryilmaz & Kadir Sarikaya, 2014. "Modeling and analysis of weighted-k-out-of-n: G system consisting of two different types of components," Journal of Risk and Reliability, , vol. 228(3), pages 265-271, June.
    9. Zhang, Nan & Fouladirad, Mitra & Barros, Anne, 2019. "Reliability-based measures and prognostic analysis of a K-out-of-N system in a random environment," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1120-1131.
    10. Mohd Ikhwan Muhammad Ridzuan & Sasa Z. Djokic, 2019. "Energy Regulator Supply Restoration Time," Energies, MDPI, vol. 12(6), pages 1-16, March.
    11. Xiaogang Song & Zhengjun Zhai & Yangming Guo & Peican Zhu & Jie Han, 2017. "Approximate Analysis of Multi-State Weighted k -Out-of- n Systems Applied to Transmission Lines," Energies, MDPI, vol. 10(11), pages 1-16, October.
    12. Serkan Eryilmaz & Ali Riza Bozbulut, 2019. "Reliability analysis of weighted- k -out-of- n system consisting of three-state components," Journal of Risk and Reliability, , vol. 233(6), pages 972-977, December.
    13. Mo, Yuchang & Xing, Liudong & Amari, Suprasad V. & Bechta Dugan, Joanne, 2015. "Efficient analysis of multi-state k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 95-105.
    14. Wang, Chaonan & Xing, Liudong & Amari, Suprasad V. & Tang, Bo, 2020. "Efficient reliability analysis of dynamic k-out-of-n heterogeneous phased-mission systems," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    15. Roy Cerqueti, 2022. "A new concept of reliability system and applications in finance," Annals of Operations Research, Springer, vol. 312(1), pages 45-64, May.
    16. Ruiz-Castro, Juan Eloy & Li, Quan-Lin, 2011. "Algorithm for a general discrete k-out-of-n: G system subject to several types of failure with an indefinite number of repairpersons," European Journal of Operational Research, Elsevier, vol. 211(1), pages 97-111, May.
    17. Xiaojun Liang & Yinghui Tang, 2019. "The improvement upon the reliability of the k-out-of-n:F system with the repair rates differentiation policy," Operational Research, Springer, vol. 19(2), pages 479-500, June.
    18. Coit, David W. & Chatwattanasiri, Nida & Wattanapongsakorn, Naruemon & Konak, Abdullah, 2015. "Dynamic k-out-of-n system reliability with component partnership," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 82-92.
    19. Jørgen Vitting Andersen & Roy Cerqueti & Jessica Riccioni, 2023. "Rational expectations as a tool for predicting failure of weighted k-out-of-n reliability systems," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03634370, HAL.
    20. Jørgen Vitting Andersen & Roy Cerqueti & Jessica Riccioni, 2023. "Rational expectations as a tool for predicting failure of weighted k-out-of-n reliability systems," Post-Print hal-03634370, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:risrel:v:237:y:2023:i:6:p:1031-1047. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.