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Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: A simulation-based optimization approach

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  • Guilani, Pedram Pourkarim
  • Azimi, Parham
  • Niaki, S.T.A.
  • Niaki, Seyed Armin Akhavan

Abstract

The redundancy allocation problem (RAP) is a useful method to enhance system reliability. In most works involving RAP, failure rates of the system components are assumed to follow either exponential or k-Erlang distributions. In real world problems however, many systems have components with increasing failure rates. This indicates that as time passes by, the failure rates of the system components increase in comparison to their initial failure rates. In this paper, the redundancy allocation problem of a series–parallel system with components having an increasing failure rate based on Weibull distribution is investigated. An optimization method via simulation is proposed for modeling and a genetic algorithm is developed to solve the problem.

Suggested Citation

  • Guilani, Pedram Pourkarim & Azimi, Parham & Niaki, S.T.A. & Niaki, Seyed Armin Akhavan, 2016. "Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: A simulation-based optimization approach," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 187-196.
    • Handle: RePEc:eee:reensy:v:152:y:2016:i:c:p:187-196
    DOI: 10.1016/j.ress.2016.03.010
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    References listed on IDEAS

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    1. Kong, Xiangyong & Gao, Liqun & Ouyang, Haibin & Li, Steven, 2015. "Solving the redundancy allocation problem with multiple strategy choices using a new simplified particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 147-158.
    2. Chambari, Amirhossain & Najafi, Amir Abbas & Rahmati, Seyed Habib A. & Karimi, Aida, 2013. "An efficient simulated annealing algorithm for the redundancy allocation problem with a choice of redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 158-164.
    3. Safari, Jalal, 2012. "Multi-objective reliability optimization of series-parallel systems with a choice of redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 10-20.
    4. 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.
    5. Zhang, Enze & Wu, Yifei & Chen, Qingwei, 2014. "A practical approach for solving multi-objective reliability redundancy allocation problems using extended bare-bones particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 65-76.
    6. Tavakkoli-Moghaddam, R. & Safari, J. & Sassani, F., 2008. "Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 550-556.
    7. Dolatshahi-Zand, Ali & Khalili-Damghani, Kaveh, 2015. "Design of SCADA water resource management control center by a bi-objective redundancy allocation problem and particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 11-21.
    8. Zhang, Enze & Chen, Qingwei, 2016. "Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 83-92.
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    Cited by:

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    7. Karimi, Behzad & Niaki, S.T.A. & Haleh, Hassan & Naderi, Bahman, 2018. "Bi-objective optimization of a job shop with two types of failures for the operating machines that use automated guided vehicles," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 92-104.
    8. Ali Salmasnia & Sadegh Noori & Hadi Mokhtari, 2019. "A redundancy allocation problem by using utility function method and ant colony optimization: tradeoff between availability and total cost," 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. 10(3), pages 416-428, June.
    9. Fiondella, Lance & Lin, Yi-Kuei & Pham, Hoang & Chang, Ping-Chen & Li, Chendong, 2017. "A confidence-based approach to reliability design considering correlated failures," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 102-114.
    10. 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.
    11. 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).
    12. Behzad Karimi & Seyed Taghi Akhavan Niaki & Amir Hossein Niknamfar & Mahsa Gareh Hassanlu, 2021. "Multi-objective optimization of job shops with automated guided vehicles: A non-dominated sorting cuckoo search algorithm," Journal of Risk and Reliability, , vol. 235(2), pages 306-328, April.
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