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A note on a reliability redundancy allocation problem using a tuned parameter genetic algorithm

Author

Listed:
  • Amirhossain Chambari

    (Islamic Azad University)

  • Javad Sadeghi

    (State University of New York at Binghamton)

  • Fakhri Bakhtiari

    (Payame Noor University)

  • Reza Jahangard

    (Islamic Azad University)

Abstract

This paper presents an improved continuous genetic algorithm (CGA) to optimize the reliability redundancy allocation problem (RRAP) which determines the best redundancy strategies, the number of components, and levels of each subsystem to maximize the system reliability. In this system, both active and cold-standby redundancies can be chosen for individual subsystems. The RRAP belongs to NP-hard problems in the computational complexity theory that is the main reason for employing CGA to solve it. In addition, the response surface methodology (RSM) is used to increase the performance of CGA considering the design of experiments. This algorithm employs a new chromosome so that frees offspring to repair during the evolution process. Considering several numerical examples, the proposed algorithm presents better solutions than the previous studies based on the system reliability. Finally, the conclusion and future research are considered.

Suggested Citation

  • Amirhossain Chambari & Javad Sadeghi & Fakhri Bakhtiari & Reza Jahangard, 2016. "A note on a reliability redundancy allocation problem using a tuned parameter genetic algorithm," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 426-442, June.
    • Handle: RePEc:spr:opsear:v:53:y:2016:i:2:d:10.1007_s12597-015-0230-9
    DOI: 10.1007/s12597-015-0230-9
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    References listed on IDEAS

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    5. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2014. "Cold vs. hot standby mission operation cost minimization for 1-out-of-N systems," European Journal of Operational Research, Elsevier, vol. 234(1), pages 155-162.
    6. Wells, Charles E., 2014. "Reliability analysis of a single warm-standby system subject to repairable and nonrepairable failures," European Journal of Operational Research, Elsevier, vol. 235(1), pages 180-186.
    7. Nachiappan, S.P. & Jawahar, N., 2007. "A genetic algorithm for optimal operating parameters of VMI system in a two-echelon supply chain," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1433-1452, November.
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    Cited by:

    1. Soheil Azizi & Milad Mohammadi, 2023. "Strategy selection for multi-objective redundancy allocation problem in a k-out-of-n system considering the mean time to failure," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 1021-1044, June.

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