Reliability evaluation in terms of flow data mining for multistate networks

Yi-Kuei Lin () and Shin-Guang Chen ()
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Yi-Kuei Lin: National Chiao Tung University
Shin-Guang Chen: Tungnan University

Annals of Operations Research, 2022, vol. 311, issue 1, No 16, 225-237

Abstract: Abstract Network reliability is famous for its problem solving ability in several real-life applications. However, due to its NP-hard nature (Ball in IEEE Trans Reliab 35(3):230–238, 1986), researchers are devoted to the improvement of computational efficiency in various approaches. Although flow in networks depicts its combination properties, only few of them are useful in the calculation of network reliability. In some point of views, we call it mining in flow data. This paper presents techniques of how to efficiently do the flow data mining tasks. A skill based on backtrack and maximal flow is illustrated with examples and benchmarks. The results show that the proposed approach is valuable in the calculation of network reliability.

Keywords: Flow data mining; Minimum path; Lower boundary vectors; Exact enumeration; Maximum flow (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-020-03774-7

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