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All issues Volume 60 / No 3 (May-June 2026) RAIRO-Oper. Res., 60 3 (2026) 1733-1755 References
Open Access
Issue
RAIRO-Oper. Res.
Volume 60, Number 3, May-June 2026
Page(s) 1733 - 1755
DOI https://doi.org/10.1051/ro/2026038
Published online 19 June 2026
  • Q.F. He, Z.T. Wang, M.F. Zheng and L. Yan, An artificial bee colony algorithm for multiobjective redundancy allocation problem in repairable system. Appl. Mech. Mater. 519 (2014) 1401–1404. [Google Scholar]
  • D.E. Fyffe, W.W. Hines and N.K. Lee, System reliability allocation and a computational algorithm. IEEE Trans. Reliab. 17 (1968) 64–69. [Google Scholar]
  • W.C. Yeh, Y.Z. Su, X.Z. Gao, C.F. Hu, J. Wang and C.L. Huang, Simplified swarm optimization for bi-objection active reliability redundancy allocation problems. Appl. Soft Comput. 106 (2021) 107321. [Google Scholar]
  • T.P. Talafuse and E.A. Pohl, A bat algorithm for the redundancy allocation problem. Eng. Optim. 48 (2016) 900–910. [Google Scholar]
  • A. Salmasnia, E. Ameri and S.T. Niaki, A robust loss function approach for a multi-objective redundancy allocation problem. Appl. Math. Model. 40 (2016) 635–645. [Google Scholar]
  • W.C. Yeh, BAT-based algorithm for finding all Pareto solutions of the series–parallel redundancy allocation problem with mixed components. Reliab. Eng. Syst. Saf. 228 (2022) 108795. [Google Scholar]
  • S.A. Mousavi, A.Z. Hamadani and H. Gholinezhad, Reliability modeling for degrading systems subject to random direct shocks transmitted between components. Qual. Reliab. Eng. Int. 41 (2025) 3736–3745. [Google Scholar]
  • D.W. Coit, Cold-standby redundancy optimization for nonrepairable systems. IIE Trans. 33 (2001) 471–478. [Google Scholar]
  • M.R. Valaei and J. Behnamian, Allocation and sequencing in 1-out-of-N heterogeneous cold-standby systems: multiobjective harmony search with dynamic parameters tuning. Reliab. Eng. Syst. Saf. 157 (2017) 78–86. [Google Scholar]
  • T.J. Hsieh, Component mixing with a cold standby strategy for the redundancy allocation problem. Reliab. Eng. Syst. Saf. 206 (2021) 107290. [Google Scholar]
  • G. Levitin, L. Xing and Y. Dai, Heterogeneous non-repairable warm standby systems with periodic inspections. IEEE Trans. Reliab. 65 (2015) 394–409. [Google Scholar]
  • F. Kayedpour, M. Amiri, M. Rafizadeh and A.S. Nia, Multi-objective redundancy allocation problem for a system with repairable components considering instantaneous availability and strategy selection. Reliab. Eng. Syst. Saf. 160 (2017) 11–20. [Google Scholar]
  • M.A. Ardakan and A.Z. Hamadani, Reliability optimization of series–parallel systems with mixed redundancy strategy in subsystems. Reliab. Eng. Syst. Saf. 130 (2014) 132–139. [Google Scholar]
  • E. Zio and H. Gholinezhad, Redundancy allocation of components with time-dependent failure rates. Mathematics 11 (2023) 3534. [CrossRef] [Google Scholar]
  • N. Mahdavi-Nasab, M.A. Ardakan and A. Peiravi, A new model for the reliability-redundancy allocation problem with the mixed redundancy strategy. J. Stat. Comput. Simul. 92 (2022) 2956–2979. [Google Scholar]
  • N.H. Zavieh, M.A. Ardakan and H. Davari-Ardakani, A new model for the reliability-redundancy allocation problem under the K-mixed redundancy strategy. J. Stat. Comput. Simul. 92 (2022) 3542–3560. [Google Scholar]
  • H. Gholinezhad, A new model for reliability redundancy allocation problem with component mixing. Reliab. Eng. Syst. Saf. 242 (2024) 109815. [Google Scholar]
  • D.W. Coit, Maximization of system reliability with a choice of redundancy strategies. IIE Trans. 35 (2003) 535–543. [Google Scholar]
  • M. Aghaei, A. Zeinal Hamadani and M. Abouei Ardakan, Redundancy allocation problem for k-out-of-n systems with a choice of redundancy strategies. J. Ind. Eng. Int. 13 (2017) 81–92. [Google Scholar]
  • X. Kong, L. Gao, H. Ouyang and S. Li, Solving the redundancy allocation problem with multiple strategy choices using a new simplified particle swarm optimization. Reliab. Eng. Syst. Saf. 144 (2015) 147–158. [Google Scholar]
  • M. Abouei Ardakan, M. Sima, A. Zeinal Hamadani and D.W. Coit, A novel strategy for redundant components in reliability–redundancy allocation problems. IIE Trans. 48 (2016) 1043–1057. [Google Scholar]
  • S. Azizi and M. Mohammadi, Strategy selection for multi-objective redundancy allocation problem in a k-out-of-n system considering the mean time to failure. Opsearch 60 (2023) 1021–1044. [Google Scholar]
  • H. Gholinezhad and R. Khosravi, A new approach to improve system reliability by eliminating early failures. J. Data Anal. Intell. Decis.-Making 1 (2025) 1–12. [Google Scholar]
  • C.M. Lai and W.C. Yeh, Two-stage simplified swarm optimization for the redundancy allocation problem in a multi-state bridge system. Reliab. Eng. Syst. Saf. 156 (2016) 148–158. [Google Scholar]
  • H. Zhang, M. Sun and Y.F. Li, Reliability–redundancy allocation problem in multi-state flow network: minimal cut-based approximation scheme. Reliab. Eng. Syst. Saf. 225 (2022) 108564. [Google Scholar]
  • Y.F. Li and H. Zhang, The methods for exactly solving redundancy allocation optimization for multi-state series–parallel systems. Reliab. Eng. Syst. Saf. 221 (2022) 108340. [Google Scholar]
  • Y. Xu, D. Pi, S. Yang and Y. Chen, A novel discrete bat algorithm for heterogeneous redundancy allocation of multi-state systems subject to probabilistic common-cause failure. Reliab. Eng. Syst. Saf. 208 (2021) 107338. [Google Scholar]
  • J. Li, G. Wang, H. Zhou and H. Chen, Redundancy allocation optimization for multi-state system with hierarchical performance requirements. Proc. Inst. Mech. Eng. Part O: J. Risk Reliab. 237 (2023) 1031–1047. [Google Scholar]
  • Z. Chen, H. Zhang, X. Wang, J. Yang and H. Dui, Reliability analysis and redundancy design of satellite communication system based on a novel Bayesian environmental importance. Reliab. Eng. Syst. Saf. 243 (2024) 109813. [Google Scholar]
  • M. Fayyaz and T. Vladimirova, Survey and future directions of fault-tolerant distributed computing on board spacecraft. Adv. Space Res. 58 (2016) 2352–2375. [Google Scholar]
  • J. Downer, When Failure is an Option: Redundancy, Reliability and Regulation in Complex Technical Systems (No. DP 53). ESRC Centre for Analysis of Risk and Regulation (2009). [Google Scholar]
  • I. Moir, A. Seabridge and M. Jukes, Civil Avionics Systems, 2nd edition. Wiley (2019). [Google Scholar]
  • Q. Zhang, M. Chen, L. Li and W. Yi, Reliability modeling and evaluation of modular UPS systems in data centers. IEEE Trans. Reliab. 67 (2018) 1615–1627. [Google Scholar]
  • D. Xun, C. Xin and J. Wenyi, The analysis of GSM-R redundant network and reliability models on high-speed railway, in 2010 International Conference on Electronics and Information Engineering. Vol. 2. IEEE (2010) V2-154. [Google Scholar]
  • I.A. Hansen and J. Pachl, Railway Timetabling and Operations: Analysis, Modelling, Optimisation. Eurailpress (2014). [Google Scholar]
  • International Electrotechnical Commission, IEC 60601-1: Medical electrical equipment – Part 1: General requirements for basic safety and essential performance. IEC (2012). [Google Scholar]
  • B. Han, V. Gopalakrishnan, L. Ji and S. Lee, Network function virtualization: challenges and opportunities for innovations. IEEE Commun. Mag. 53 (2015) 90–97. [Google Scholar]
  • J.H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. MIT Press (1992). [Google Scholar]
  • K. Deb, A. Pratap, S. Agarwal and T.A. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6 (2002) 182–197. [CrossRef] [Google Scholar]
  • D. Salazar, C.M. Rocco and B.J. Galván, Optimization of constrained multiple-objective reliability problems using evolutionary algorithms. Reliab. Eng. Syst. Saf. 91 (2006) 1057–1070. [Google Scholar]

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