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A penalty guided stochastic fractal search approach for system reliability optimization

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  • Mellal, Mohamed Arezki
  • Zio, Enrico

Abstract

Modern industry requires components and systems with high reliability levels. In this paper, we address the system reliability optimization problem. A penalty guided stochastic fractal search approach is developed for solving reliability allocation, redundancy allocation, and reliability–redundancy allocation problems. Numerical results of ten case studies are presented as benchmark problems for highlighting the superiority of the proposed approach compared to others from literature.

Suggested Citation

  • Mellal, Mohamed Arezki & Zio, Enrico, 2016. "A penalty guided stochastic fractal search approach for system reliability optimization," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 213-227.
  • Handle: RePEc:eee:reensy:v:152:y:2016:i:c:p:213-227
    DOI: 10.1016/j.ress.2016.03.019
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    References listed on IDEAS

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    1. Zio, E., 2009. "Reliability engineering: Old problems and new challenges," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 125-141.
    2. Gen, Mitsuo & Yun, YoungSu, 2006. "Soft computing approach for reliability optimization: State-of-the-art survey," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1008-1026.
    3. Huang, Chia-Ling, 2015. "A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 221-230.
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