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The methods for exactly solving redundancy allocation optimization for multi-state series–parallel systems

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  • Li, Yan-Fu
  • Zhang, Hanxiao

Abstract

Redundancy allocation problems (RAPs) is a classical family of reliability optimization problems. RAP for multi-state systems (MSSs) is among the most difficult RAPs. Multi-state series–parallel system (MSSPS) is among the most commonly-applied structure of MSSs. To the knowledge of the authors, in literature there is no exact approach to solve MSSPS RAP. In this work, we propose an efficient exact solution method based on dynamic programming to solve it. In literature, there are two formulations of RAP, namely maximizing the system reliability and minimizing of the system cost under the resource constraints. In this work, we investigate the conversion between the two formulations such that the two different RAP formulations can be exactly solved via our proposed method. Experiments are conducted on the well-known benchmarks. The results are compared with the published ones achieved by meta-heuristics. Our methods confirm that majority of the published solutions are in fact global-optimal. In addition, our methods find three new global-optimal solutions. The experiments also illustrate that on systems with more subsystems and fewer component types, our proposed method significantly outperforms the heuristic method in MSSPS RAP with exact optimal solutions and less running time.

Suggested Citation

  • Li, Yan-Fu & Zhang, Hanxiao, 2022. "The methods for exactly solving redundancy allocation optimization for multi-state series–parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
  • Handle: RePEc:eee:reensy:v:221:y:2022:i:c:s0951832022000205
    DOI: 10.1016/j.ress.2022.108340
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    References listed on IDEAS

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    Cited by:

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    3. Xu, Dong & Tian, Yubin & Shi, Junbiao & Wang, Dianpeng & Zhang, Ming & Li, Haijin, 2023. "Reliability analysis and optimal redundancy for a satellite power supply system based on a new dynamic k-out-of-n: G model," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    4. Zhou, Jian & Coit, David W. & Felder, Frank A. & Tsianikas, Stamatis, 2023. "Combined optimization of system reliability improvement and resilience with mixed cascading failures in dependent network systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    5. Sharifi, Mani & Taghipour, Sharareh, 2024. "Redundancy allocation problem with a mix of components for a multi-state system and continuous performance level components," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    6. Zhang, Hanxiao & Sun, Muxia & Li, Yan-Fu, 2022. "Reliability–redundancy allocation problem in multi-state flow network: Minimal cut-based approximation scheme," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    7. Zhang, Zixuan & Yang, Lin & Xu, Youwei & Zhu, Ran & Cao, Yining, 2023. "A novel reliability redundancy allocation problem formulation for complex systems," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    8. Yeh, Wei-Chang, 2022. "BAT-based algorithm for finding all Pareto solutions of the series-parallel redundancy allocation problem with mixed components," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. Kowal, Karol, 2022. "Lifetime reliability and availability simulation for the electrical system of HTTR coupled to the electricity-hydrogen cogeneration plant," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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