Importance measures in reliability and mathematical programming
Importance measures in reliability and mathematical programming
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DOI：
10.1007/s10479-012-1127-0
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发表时间：
2014
影响因子：
4.8
通讯作者：
Xiaoyan Zhu;W. Kuo
中科院分区：
文献类型：
--
作者：
Xiaoyan Zhu;W. Kuo
重要性度量是概率系统的敏感性分析，并与其他设计工具一起应用于不同领域。本文对解决组件分配问题、冗余分配、系统升级、故障诊断和维护等可靠性问题的重要措施进行建模提供了全面的视角。它还研究了网络、数学规划、敏感性和不确定性分析以及概率风险分析和概率安全评估等广泛应用中的重要性度量。基于重要性度量的方法是最实用的决策工具之一。
The importance measures have been a sensitivity analysis for a probabilistic system and are applied in diverse fields along with other design tools. This paper provides a comprehensive view on modeling the importance measures to solve the reliability problems such as component assignment problems, redundancy allocation, system upgrading, and fault diagnosis and maintenance. It also investigates importance measures in broad applications such as networks, mathematical programming, sensitivity and uncertainty analysis, and probabilistic risk analysis and probabilistic safety assessment. The importance-measure based methods are among the most practical decision tools.