最优修复策略的参数NdRFT推导

M. Beccuti, G. Franceschinis, D. Raiteri, S. Haddad
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引用次数: 4

摘要

非确定性可修复故障树(NdRFT)是最近提出的一种用于研究最优修复策略的建模形式:它们基于广泛采用的故障树形式,但除了故障模式外,NdRFT还允许定义可能的修复动作。在之前的一篇文章中,已经介绍了形式主义以及一种分析方法和一种工具,可以自动导出在每种状态下应用的最佳修复策略。该分析技术基于马尔可夫决策过程的生成和求解。在本文中,我们提出了一个扩展,ParNdRFT,它允许利用冗余的存在来降低模型和分析的复杂性。它基于将ParNdRFT转换为马尔可夫决策良构网,即通过高级Petri网形式主义指定的模型。由于现有的算法可以自动利用模型对称性生成简化的状态空间,因此可以有效地求解平移模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parametric NdRFT for the derivation of optimal repair strategies
Non deterministic Repairable Fault Trees (NdRFT) are a recently proposed modeling formalism for the study of optimal repair strategies: they are based on the widely adopted Fault Tree formalism, but in addition to the failure modes, NdRFTs allow to define possible repair actions. In a previous pa per the formalism has been introduced together with an analysis method and a tool allowing to automatically derive the best repair strategy to be applied in each state. The analysis technique is based on the generation and solution of a Markov Decision Process. In this paper we present an extension, ParNdRFT, that allows to exploit the presence of redundancy to reduce the complexity of the model and of the analysis. It is based on the translation of the ParNdRFT in to a Markov Decision Well-Formed Net, i.e. a model specified by means of an High Level Petri Net formalism. The translated model can be efficiently solved thanks to existing algorithms that generate a reduced state space automatically exploiting the model symmetries.
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