IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v92y2007i10p1435-1447.html
   My bibliography  Save this article

Importance measures and genetic algorithms for designing a risk-informed optimally balanced system

Author

Listed:
  • Zio, Enrico
  • Podofillini, Luca

Abstract

This paper deals with the use of importance measures for the risk-informed optimization of system design and management. An optimization approach is presented in which the information provided by the importance measures is incorporated in the formulation of a multi-objective optimization problem to drive the design towards a solution which, besides being optimal from the points of view of economics and safety, is also ‘balanced’ in the sense that all components have similar importance values. The approach allows identifying design systems without bottlenecks or unnecessarily high-performing components and with test/maintenance activities calibrated according to the components’ importance ranking. The approach is tested at first against a multi-state system design optimization problem in which off-the-shelf components have to be properly allocated. Then, the more realistic problem of risk-informed optimization of the technical specifications of a safety system of a nuclear power plant is addressed.

Suggested Citation

  • Zio, Enrico & Podofillini, Luca, 2007. "Importance measures and genetic algorithms for designing a risk-informed optimally balanced system," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1435-1447.
    • Handle: RePEc:eee:reensy:v:92:y:2007:i:10:p:1435-1447
    DOI: 10.1016/j.ress.2006.09.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832006002043
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2006.09.011?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Podofillini, Luca & Zio, Enrico, 2008. "Designing a risk-informed balanced system by genetic algorithms: Comparison of different balancing criteria," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1842-1852.
    2. Whitson, John C. & Ramirez-Marquez, Jose Emmanuel, 2009. "Resiliency as a component importance measure in network reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1685-1693.
    3. Chenxi Liu & Nan Chen & Jianing Yang, 2015. "New method for multi-state system reliability analysis based on linear algebraic representation," Journal of Risk and Reliability, , vol. 229(5), pages 469-482, October.
    4. Mancuso, A. & Compare, M. & Salo, A. & Zio, E., 2017. "Portfolio optimization of safety measures for reducing risks in nuclear systems," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 20-29.
    5. Lin, Chaochao & Song, Junho & Pozzi, Matteo, 2022. "Optimal inspection of binary systems via Value of Information analysis," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    6. Cristina Johansson & Johan Ölvander & Micael Derelöv, 2018. "Multi-objective optimization for safety and reliability trade-off: Optimization and results processing," Journal of Risk and Reliability, , vol. 232(6), pages 661-676, December.
    7. Zhang, Sai & Du, Mengyu & Tong, Jiejuan & Li, Yan-Fu, 2019. "Multi-objective optimization of maintenance program in multi-unit nuclear power plant sites," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 532-548.
    8. Compare, Michele & Bellani, Luca & Zio, Enrico, 2019. "Optimal allocation of prognostics and health management capabilities to improve the reliability of a power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 164-180.

    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:eee:reensy:v:92:y:2007:i:10:p:1435-1447. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.