Efficient Combinatorial Models for Reliability Analysis of Complex Dynamic Systems (基于组合模型的复杂动态系统可靠性分析)

Liudong Xing
Dr. Liudong Xing is a tenured Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts (UMass), Dartmouth. She received her PhD degree in Electrical Engineering from the University of Virginia in 2002. Her current research focuses on reliability modeling and analysis of complex systems and networks. Dr. Xing’s research has been supported by the US Nat...read more



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In the area of system reliability analysis, dynamic and dependent behaviors such as multi-state, multi-phase, functional dependence, common cause failures, competing failures, standby sparing, and sequence dependence have been recognized as a significant contribution to problems in overall system reliability. However, with the incorporation of those behaviors, resulting dynamic system reliability models cannot be efficiently and accurately solved by existing state space based models such as Markov methods. In this presentation, an overview on various dynamic and dependent behaviors will be presented first. Efficient combinatorial approaches, in particular, decision diagrams will then be discussed for the reliability analysis of multi-state systems with illustration of examples from areas of computer systems, capacitated transmission networks, and MCNC benchmark circuits.

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