IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v238y2024i1p136-157.html
   My bibliography  Save this article

A sequential two-stage approach based on variational Bayesian inference for reliability-redundancy allocation

Author

Listed:
  • Chunyan Ling
  • Jingzhe Lei
  • Way Kuo

    (Department of Advanced Design and Systems Engineering, City University of Hong Kong, Hong Kong, China)

Abstract

The reliability-related design has been a crucial chain in complex and reliability-critical engineering systems. It serves as a preventive countermeasure to catastrophic failures caused by uncertainties. To keep up with this rapidly developing field, this paper presents a novel metaheuristic, based on the variational Bayesian inference (VBI) to efficiently solve the optimal reliability design. Specifically, the reliability-redundancy allocation problem (RRAP). The proposed metaheuristic starts from a primary population, then leverages VBI to fully excavate the information of feasible individuals from the previous generation, in order to produce the next-generation population. This process is iterated until the solution converges to the optimal decision scheme. In addition, we set up an automatic stratification strategy, so that the new individuals can approach the optimal solution faster. Furthermore, we divide RRAP into a reliability optimization problem (ROP) and a redundancy allocation problem (RAP). This not only reduces the dimension of decision variables, but also speeds up the convergence. ROP and RAP are solved sequentially and iteratively until the preset stopping condition is satisfied. The case studies showcase that the proposed approach can obtain the optimal or near-optimal solution within a reasonable period.

Suggested Citation

  • Chunyan Ling & Jingzhe Lei & Way Kuo, 2024. "A sequential two-stage approach based on variational Bayesian inference for reliability-redundancy allocation," Journal of Risk and Reliability, , vol. 238(1), pages 136-157, February.
    • Handle: RePEc:sae:risrel:v:238:y:2024:i:1:p:136-157
    DOI: 10.1177/1748006X221130123
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X221130123
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X221130123?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. Kim, Heungseob & Kim, Pansoo, 2017. "Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 153-160.
    2. Sedaghat, Niloofar & Ardakan, Mostafa Abouei, 2021. "G-mixed: A new strategy for redundant components in reliability optimization problems," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    3. Seyed Mohsen Mousavi & Najmeh Alikar & Madjid Tavana & Debora Di Caprio, 2019. "An improved particle swarm optimization model for solving homogeneous discounted series-parallel redundancy allocation problems," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1175-1194, March.
    4. Mostafa Abouei Ardakan & Mohammad Sima & Ali Zeinal Hamadani & David W. Coit, 2016. "A novel strategy for redundant components in reliability--redundancy allocation problems," IISE Transactions, Taylor & Francis Journals, vol. 48(11), pages 1043-1057, November.
    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. 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).
    2. Hsieh, Tsung-Jung, 2023. "A Q-learning guided search for developing a hybrid of mixed redundancy strategies to improve system reliability," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    3. Zaretalab, Arash & Sharifi, Mani & Guilani, Pedram Pourkarim & Taghipour, Sharareh & Niaki, Seyed Taghi Akhavan, 2022. "A multi-objective model for optimizing the redundancy allocation, component supplier selection, and reliable activities for multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    4. Ling, Chunyan & Yang, Lechang & Feng, Kaixuan & Kuo, Way, 2023. "Survival signature based robust redundancy allocation under imprecise probability," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    5. Gholinezhad, Hadi & Zeinal Hamadani, Ali, 2017. "A new model for the redundancy allocation problem with component mixing and mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 66-73.
    6. Ouyang, Zhiyuan & Liu, Yu & Ruan, Sheng-Jia & Jiang, Tao, 2019. "An improved particle swarm optimization algorithm for reliability-redundancy allocation problem with mixed redundancy strategy and heterogeneous components," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 62-74.
    7. Peiravi, Abdossaber & Nourelfath, Mustapha & Zanjani, Masoumeh Kazemi, 2022. "Redundancy strategies assessment and optimization of k-out-of-n systems based on Markov chains and genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    8. Wang, Wei & Wu, Zhiying & Xiong, Junlin & Xu, Yaofeng, 2018. "Redundancy optimization of cold-standby systems under periodic inspection and maintenance," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 394-402.
    9. Li, Yan-Fu & Zhang, Hanxiao, 2022. "The methods for exactly solving redundancy allocation optimization for multi-state series–parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    10. Anushri Maji & Asoke Kumar Bhunia & Shyamal Kumar Mondal, 2022. "A production-reliability-inventory model for a series-parallel system with mixed strategy considering shortage, warranty period, credit period in crisp and stochastic sense," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 862-907, September.
    11. Hsieh, Tsung-Jung, 2023. "Performance indicator-based multi-objective reliability optimization for multi-type production systems with heterogeneous machines," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    12. Guilani, Pardis Pourkarim & Juybari, Mohammad N. & Ardakan, Mostafa Abouei & Kim, Heungseob, 2020. "Sequence optimization in reliability problems with a mixed strategy and heterogeneous backup scheme," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    13. Peiravi, Abdossaber & Ardakan, Mostafa Abouei & Zio, Enrico, 2020. "A new Markov-based model for reliability optimization problems with mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    14. Wang, Wei & Lin, Mingqiang & Fu, Yongnian & Luo, Xiaoping & Chen, Hanghang, 2020. "Multi-objective optimization of reliability-redundancy allocation problem for multi-type production systems considering redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    15. Xiang, Jianwen & Wang, Zixiang & Wu, Chuanli & Zhao, Dongdong & Tian, Jing, 2022. "Optimal redundancies of parallel–series systems in irrelevancy coverage model," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    16. Peiravi, Abdossaber & Nourelfath, Mustapha & Zanjani, Masoumeh Kazemi, 2022. "Universal redundancy strategy for system reliability optimization," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    17. de Paula, Cassio Pereira & Visnadi, Lais Bittencourt & de Castro, Helio Fiori, 2019. "Multi-objective optimization in redundant system considering load sharing," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 17-27.
    18. Muhuri, Pranab K. & Nath, Rahul, 2019. "A novel evolutionary algorithmic solution approach for bilevel reliability-redundancy allocation problem," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    19. Saeideh Sheikhpour & Amin Kargar-Barzi & Ali Mahani, 2022. "A novel component mixing and mixed redundancy strategy for reliability optimization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 328-346, February.
    20. Nath, Rahul & Muhuri, Pranab K., 2024. "A novel evolutionary solution approach for many-objective reliability-redundancy allocation problem based on objective prioritization and constraint optimization," Reliability Engineering and System Safety, Elsevier, vol. 244(C).

    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:238:y:2024:i:1:p:136-157. 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.