IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v233y2019i4p658-669.html
   My bibliography  Save this article

Redundancy allocation problem in a bridge system with dependent subsystems

Author

Listed:
  • Kamyar Sabri-Laghaie
  • Milad Eshkevari
  • Mahdi Fathi
  • Enrico Zio

Abstract

The redundancy allocation problem is an important problem in system reliability design. Many researchers have investigated the redundancy allocation problem under different assumptions and for various system configurations. However, most of the studies have disregarded the dependence among components and subsystems. In real-world applications, the performance of components and subsystems can affect each others. For instance, the heat radiated by a subsystem can accelerate degradation of adjacent components or subsystems. In this article, a procedure is proposed for solving the redundancy allocation problem of a bridge structure with dependent subsystems. Copula theory is utilized for modeling dependence among subsystems, and artificial neural network and particle swarm optimization are applied for finding the best redundancy allocation. A numerical example is included to elaborate the proposed procedure and show its applicability.

Suggested Citation

  • Kamyar Sabri-Laghaie & Milad Eshkevari & Mahdi Fathi & Enrico Zio, 2019. "Redundancy allocation problem in a bridge system with dependent subsystems," Journal of Risk and Reliability, , vol. 233(4), pages 658-669, August.
    • Handle: RePEc:sae:risrel:v:233:y:2019:i:4:p:658-669
    DOI: 10.1177/1748006X18814627
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X18814627
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X18814627?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. Abouei Ardakan, Mostafa & Rezvan, Mohammad Taghi, 2018. "Multi-objective optimization of reliability–redundancy allocation problem with cold-standby strategy using NSGA-II," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 225-238.
    2. Yinping You & Xiaohu Li, 2014. "On allocating redundancies to k‐out‐of‐ n reliability systems," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 30(3), pages 361-371, May.
    3. Sadjadi, Seyed Jafar & Soltani, R., 2009. "An efficient heuristic versus a robust hybrid meta-heuristic for general framework of serial–parallel redundancy problem," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1703-1710.
    4. Singh, Nitin & Mohanty, Soumya Ranjan & Dev Shukla, Rishabh, 2017. "Short term electricity price forecast based on environmentally adapted generalized neuron," Energy, Elsevier, vol. 125(C), pages 127-139.
    5. Hamideh Jeddi & Mahdi Doostparast, 2016. "Optimal redundancy allocation problems in engineering systems with dependent component lifetimes," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 32(2), pages 199-208, March.
    6. Belzunce, Félix & Martínez-Puertas, Helena & Ruiz, José M., 2013. "On allocation of redundant components for systems with dependent components," European Journal of Operational Research, Elsevier, vol. 230(3), pages 573-580.
    7. da Costa Bueno, Vanderlei, 2005. "Minimal standby redundancy allocation in a k-out-of-n:F system of dependent components," European Journal of Operational Research, Elsevier, vol. 165(3), pages 786-793, September.
    8. Lai, Chyh-Ming & Yeh, Wei-Chang, 2016. "Two-stage simplified swarm optimization for the redundancy allocation problem in a multi-state bridge system," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 148-158.
    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. Navarro, Jorge & Arriaza, Antonio & Suárez-Llorens, Alfonso, 2019. "Minimal repair of failed components in coherent systems," European Journal of Operational Research, Elsevier, vol. 279(3), pages 951-964.
    2. Torrado, Nuria & Arriaza, Antonio & Navarro, Jorge, 2021. "A study on multi-level redundancy allocation in coherent systems formed by modules," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. Yinping You & Xiaohu Li & Rui Fang, 2021. "On coverage limits and deductibles for SAI loss severities," Annals of Operations Research, Springer, vol. 297(1), pages 341-357, February.
    4. Navarro, Jorge & Pellerey, Franco & Di Crescenzo, Antonio, 2015. "Orderings of coherent systems with randomized dependent components," European Journal of Operational Research, Elsevier, vol. 240(1), pages 127-139.
    5. Rui Fang & Xiaohu Li, 2016. "On allocating one active redundancy to coherent systems with dependent and heterogeneous components' lifetimes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(4), pages 335-345, June.
    6. Hsieh, Tsung-Jung, 2021. "Component mixing with a cold standby strategy for the redundancy allocation problem," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    7. Zhao, Peng & Zhang, Yiying & Chen, Jianbin, 2017. "Optimal allocation policy of one redundancy in a n-component series system," European Journal of Operational Research, Elsevier, vol. 257(2), pages 656-668.
    8. Ardakan, Mostafa Abouei & Talkhabi, Sajjad & Juybari, Mohammad N., 2022. "Optimal activation order vs. redundancy strategies in reliability optimization problems," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    9. 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).
    10. Yung-Chia Chang & Kuei-Hu Chang & Ching-Ping Zheng, 2022. "Application of a Non-Dominated Sorting Genetic Algorithm to Solve a Bi-Objective Scheduling Problem Regarding Printed Circuit Boards," Mathematics, MDPI, vol. 10(13), pages 1-21, July.
    11. Mellal, Mohamed Arezki & Zio, Enrico, 2020. "System reliability-redundancy optimization with cold-standby strategy by an enhanced nest cuckoo optimization algorithm," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    12. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Prediction and explanation of the formation of the Spanish day-ahead electricity price through machine learning regression," Applied Energy, Elsevier, vol. 239(C), pages 610-625.
    13. Navarro, Jorge & Fernández-Martínez, Pedro, 2021. "Redundancy in systems with heterogeneous dependent components," European Journal of Operational Research, Elsevier, vol. 290(2), pages 766-778.
    14. Yeh, Wei-Chang, 2017. "Evaluation of the one-to-all-target-subsets reliability of a novel deterioration-effect acyclic multi-state information network," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 132-137.
    15. Li, Shuai & Chi, Xuefen & Yu, Baozhu, 2022. "An improved particle swarm optimization algorithm for the reliability–redundancy allocation problem with global reliability," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    16. Sharifi, Mani & Taghipour, Sharareh & Abhari, Abdolreza, 2021. "Inspection interval optimization for a k-out-of-n load sharing system under a hybrid mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    17. Yeh, Wei-Chang & Chu, Ta-Chung, 2018. "A novel multi-distribution multi-state flow network and its reliability optimization problem," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 209-217.
    18. Hamideh Jeddi & Mahdi Doostparast, 2022. "Allocation of redundancies in systems: a general dependency-base framework," Annals of Operations Research, Springer, vol. 312(1), pages 259-273, May.
    19. Yin, Linfei & Qiu, Yao, 2022. "Long-term price guidance mechanism of flexible energy service providers based on stochastic differential methods," Energy, Elsevier, vol. 238(PB).
    20. Kwak, Sanghyeok & Choi, Jaehong & Lee, Min Chul & Yoon, Youngbin, 2021. "Predicting instability frequency and amplitude using artificial neural network in a partially premixed combustor," Energy, Elsevier, vol. 230(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:233:y:2019:i:4:p:658-669. 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.