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Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem

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  • Yeh, Wei-Chang

Abstract

Network structures and models have been widely adopted, e.g., for Internet of Things, wireless sensor networks, smart grids, transportation networks, communication networks, social networks, and computer grid systems. Network reliability is an effective and popular technique to estimate the probability that the network is still functioning. Networks composed of binary-state (e.g., working or failed) components (arcs and/or nodes) are called binary-state networks. The binary-state network is the fundamental type of network; thus, there is always a need for a more efficient algorithm to calculate the network reliability. Thus, a novel binary-addition tree (BAT) algorithm that employs binary addition for finding all the possible state vectors and the path-based layered-search algorithm for filtering out all the connected vectors is proposed for calculating the binary-state network reliability. According to the time complexity and numerical examples, the efficiency of the proposed BAT is higher than those of traditional algorithms for solving the binary-state network reliability problem.

Suggested Citation

  • Yeh, Wei-Chang, 2021. "Novel binary-addition tree algorithm (BAT) for binary-state network reliability problem," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    • Handle: RePEc:eee:reensy:v:208:y:2021:i:c:s095183202100017x
    DOI: 10.1016/j.ress.2021.107448
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    References listed on IDEAS

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    1. Yeh, Wei-Chang, 2006. "A simple algorithm to search for all MCs in networks," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1694-1705, November.
    2. Yeh, Wei-Chang, 2007. "An improved sum-of-disjoint-products technique for the symbolic network reliability analysis with known minimal paths," Reliability Engineering and System Safety, Elsevier, vol. 92(2), pages 260-268.
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    4. Yeh, Wei-Chang, 2006. "The k-out-of-n acyclic multistate-node networks reliability evaluation using the universal generating function method," Reliability Engineering and System Safety, Elsevier, vol. 91(7), pages 800-808.
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    6. Yeh, Wei-Chang & Bae, Changseok & Huang, Chia-Ling, 2015. "A new cut-based algorithm for the multi-state flow network reliability problem," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 1-7.
    7. Gregory Levitin, 2005. "The Universal Generating Function in Reliability Analysis and Optimization," Springer Series in Reliability Engineering, Springer, number 978-1-84628-245-4, February.
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    Citations

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    Cited by:

    1. Yeh, Wei-Chang & Tan, Shi-Yi & Forghani-elahabad, Majid & Khadiri, Mohamed El & Jiang, Yunzhi & Lin, Chen-Shiun, 2022. "New binary-addition tree algorithm for the all-multiterminal binary-state network reliability problem," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    2. Yeh, Wei-Chang & Du, Chia-Ming & Tan, Shi-Yi & Forghani-elahabad, Majid, 2023. "Application of LSTM based on the BAT-MCS for binary-state network approximated time-dependent reliability problems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    3. Wu, Baichao & Sun, Long, 2024. "A novel layer-by-layer recursive decomposition algorithm for calculation of network reliability," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    4. Yeh, Wei-Chang, 2022. "Novel direct algorithm for computing simultaneous all-level reliability of multistate flow networks," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    5. Yeh, Wei-Chang & Tan, Shi-Yi & Zhu, Wenbo & Huang, Chia-Ling & Yang, Guang-yi, 2022. "Novel binary addition tree algorithm (BAT) for calculating the direct lower-bound of the highly reliable binary-state network reliability," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    6. Chen, Liwei & Cheng, Chunchun & Dui, Hongyan & Xing, Liudong, 2022. "Maintenance cost-based importance analysis under different maintenance strategies," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    7. Hao, Zhifeng & Yeh, Wei-Chang & Tan, Shi-Yi, 2021. "One-batch preempt deterioration-effect multi-state multi-rework network reliability problem and algorithms," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    8. Yeh, Wei-Chang, 2022. "Novel self-adaptive Monte Carlo simulation based on binary-addition-tree algorithm for binary-state network reliability approximation," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. Davila-Frias, Alex & Yodo, Nita & Le, Trung & Yadav, Om Prakash, 2023. "A deep neural network and Bayesian method based framework for all-terminal network reliability estimation considering degradation," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    10. 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).
    11. Yeh, Wei-Chang, 2021. "Novel Algorithm for Computing All-Pairs Homogeneity-Arc Binary-State Undirected Network Reliability," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    12. Cui, Hongjun & Wang, Fei & Ma, Xinwei & Zhu, Minqing, 2022. "A novel fixed-node unconnected subgraph method for calculating the reliability of binary-state networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    13. Yeh, Wei-Chang & Zhu, Wenbo & Tan, Shi-Yi & Wang, Gai-Ge & Yeh, Yuan-Hui, 2022. "Novel general active reliability redundancy allocation problems and algorithm," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).

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