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Building reliable budget-based binary-state networks

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  • Yeh, Wei-Chang

Abstract

Everyday life is driven by various network, such as supply chains for distributing raw materials, semi-finished product goods, and final products; Internet of Things (IoT) for connecting and exchanging data; utility networks for transmitting fuel, power, water, electricity, and 4Â G/5Â G; and social networks for sharing information and connections. The binary-state network is a basic network, where the state of each component is either success or failure, i.e., the binary-state. Network reliability plays an important role in evaluating the performance of network planning, design, and management. Because more networks are being set up in the real world currently, there is a need for their reliability. It is necessary to build a reliable network within a limited budget. However, existing studies are focused on the budget limit for each minimal path (MP) in networks without considering the total budget of the entire network. We propose a novel concept to consider how to build a more reliable binary-state network under the budget limit. In addition, we propose an algorithm based on the binary-addition-tree algorithm (BAT) and stepwise vectors to solve the problem efficiently.

Suggested Citation

  • Yeh, Wei-Chang, 2023. "Building reliable budget-based binary-state networks," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
  • Handle: RePEc:eee:reensy:v:240:y:2023:i:c:s0951832023004817
    DOI: 10.1016/j.ress.2023.109567
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    References listed on IDEAS

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    1. Majid Forghani-elahabad & Nelson Kagan, 2019. "Reliability evaluation of a stochastic-flow network in terms of minimal paths with budget constraint," IISE Transactions, Taylor & Francis Journals, vol. 51(5), pages 547-558, May.
    2. Yi-Feng Niu & Can He & De-Qiang Fu, 2022. "Reliability assessment of a multi-state distribution network under cost and spoilage considerations," Annals of Operations Research, Springer, vol. 309(1), pages 189-208, February.
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    Cited by:

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    2. Huo, Xiaosen & Yin, Yuan & Jiao, Liudan & Zhang, Yu, 2024. "A data-driven and knowledge graph-based analysis of the risk hazard coupling mechanism in subway construction accidents," Reliability Engineering and System Safety, Elsevier, vol. 250(C).

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