Reliability evaluation in terms of flow data mining for multistate networks

被引：0
|
作者：
Yi-Kuei Lin
Shin-Guang Chen
机构：
[1] National Chiao Tung University,Department of Industrial Engineering and Management
[2] Asia University,Department of Business Administration
[3] Wenzhou University,College of Mechanical and Electrical Engineering
[4] Tungnan University,Institute of Industrial Management
[5] Kaohsiung Medical University,Department of Sports Medicine
来源：
Annals of Operations Research | 2022年 / 311卷
关键词：
Flow data mining; Minimum path; Lower boundary vectors; Exact enumeration; Maximum flow;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：225 / 237
页数：12
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