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Redundancy allocation for multi-state systems using physical programming and genetic algorithms

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  • Tian, Zhigang
  • Zuo, Ming J.

Abstract

This paper proposes a multi-objective optimization model for redundancy allocation for multi-state series–parallel systems. This model seeks to maximize system performance utility while minimizing system cost and system weight simultaneously. We use physical programming as an effective approach to optimize the system structure within this multi-objective optimization framework. The physical programming approach offers a flexible and effective way to address the conflicting nature of these different objectives. Genetic algorithm (GA) is used to solve the proposed physical programming-based optimization model due to the following three reasons: (1) the design variables, the number of components of each subsystems, are integer variables; (2) the objective functions in the physical programming-based optimization model do not have nice mathematical properties, and thus traditional optimization approaches are not suitable in this case; (3) GA has good global optimization performance. An example is used to illustrate the flexibility and effectiveness of the proposed physical programming approach over the single-objective method and the fuzzy optimization method.

Suggested Citation

  • Tian, Zhigang & Zuo, Ming J., 2006. "Redundancy allocation for multi-state systems using physical programming and genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1049-1056.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:9:p:1049-1056
    DOI: 10.1016/j.ress.2005.11.039
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    References listed on IDEAS

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    1. Richard E. Barlow & Alexander S. Wu, 1978. "Coherent Systems with Multi-State Components," Mathematics of Operations Research, INFORMS, vol. 3(4), pages 275-281, November.
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    Cited by:

    1. Huang, Xianzhen & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2019. "A heuristic survival signature based approach for reliability-redundancy allocation," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 511-517.
    2. Li, Chun-yang & Chen, Xun & Yi, Xiao-shan & Tao, Jun-yong, 2010. "Heterogeneous redundancy optimization for multi-state series–parallel systems subject to common cause failures," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 202-207.
    3. Okafor, Ekene Gabriel & Sun, You-Chao, 2012. "Multi-objective optimization of a series–parallel system using GPSIA," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 61-71.
    4. Cao, Dingzhou & Murat, Alper & Chinnam, Ratna Babu, 2013. "Efficient exact optimization of multi-objective redundancy allocation problems in series-parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 154-163.
    5. Li, Y.F. & Peng, R., 2014. "Availability modeling and optimization of dynamic multi-state series–parallel systems with random reconfiguration," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 47-57.
    6. Attar, Ahmad & Raissi, Sadigh & Khalili-Damghani, Kaveh, 2017. "A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 177-191.
    7. Li, Zhaojun & Liao, Haitao & Coit, David W., 2009. "A two-stage approach for multi-objective decision making with applications to system reliability optimization," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1585-1592.
    8. Andrés Cacereño & David Greiner & Blas J. Galván, 2021. "Multi-Objective Optimum Design and Maintenance of Safety Systems: An In-Depth Comparison Study Including Encoding and Scheduling Aspects with NSGA-II," Mathematics, MDPI, vol. 9(15), pages 1-39, July.
    9. Coelho, Leandro dos Santos, 2009. "An efficient particle swarm approach for mixed-integer programming in reliability–redundancy optimization applications," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 830-837.
    10. Tian, Zhigang & Zhang, Han, 2022. "Wind farm predictive maintenance considering component level repairs and economic dependency," Renewable Energy, Elsevier, vol. 192(C), pages 495-506.
    11. Tian, Zhigang & Levitin, Gregory & Zuo, Ming J., 2009. "A joint reliability–redundancy optimization approach for multi-state series–parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1568-1576.

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