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Combination methods to solve the availability–redundancy optimisation problem for repairable parallel–series systems

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  • Gia-Shie Liu

Abstract

This study combines a new developed redundancy allocation heuristic approach, tabu search method, simulated annealing method and non-equilibrium simulated annealing method with a genetic algorithm to solve the system availability optimisation problem. Through four proposed combination methods applied in the initial system development period, the optimal allocations of component redundancy number, reliability level and maintenance rate can be obtained to minimise the total system cost under different configuration constraints. The sensitivity analysis is also conducted based on system weight, system volume, subsystem reliability requirement levels, the cost parameters associated with the reliability level and maintenance rate to provide very helpful information for the system design and development process. Finally, the performance comparison between four proposed combination availability optimisation methods is also implemented and the results clearly show that the combination method combining the new developed redundancy allocation heuristic approach with the genetic algorithm performs better than the other three combination methods in many aspects.

Suggested Citation

  • Gia-Shie Liu, 2015. "Combination methods to solve the availability–redundancy optimisation problem for repairable parallel–series systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(12), pages 2240-2257, September.
    • Handle: RePEc:taf:tsysxx:v:46:y:2015:i:12:p:2240-2257
    DOI: 10.1080/00207721.2013.860636
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    References listed on IDEAS

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    1. Chuen-Horng Lin & Jau-Chuan Ke & Hsin-I Huang, 2012. "Reliability-based measures for a system with an uncertain parameter environment," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(6), pages 1146-1156.
    2. Chiang, Cheng-Hsiung & Chen, Liang-Hsuan, 2007. "Availability allocation and multi-objective optimization for parallel-series systems," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1231-1244, August.
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    Cited by:

    1. Gia-Shie Liu & Kuo-Ping Lin, 2022. "Availability Optimization Decision Support Design System for Different Repairable n -Stage Mixed Systems," Mathematics, MDPI, vol. 11(1), pages 1-47, December.

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