Robustness of maintenance decisions: Uncertainty modelling and value of information
Robustness of maintenance decisions: Uncertainty modelling and value of information
复制标题
DOI：
10.1016/j.ress.2013.03.001
复制
发表时间：
2013-12
期刊：
影响因子：
--
通讯作者：
A. Zitrou;T. Bedford;A. Daneshkhah
中科院分区：
文献类型：
--
作者：
A. Zitrou;T. Bedford;A. Daneshkhah
在本文中，我们展示了如何利用完全信息期望值(EVPI)的概念对维修优化问题进行灵敏度分析。这个概念在决策理论的背景下很重要，例如维修问题，因为它允许我们探索参数不确定性对成本的影响和由此产生的建议。为了减少计算EVPI所需的计算工作量，我们使用了高斯过程(GP)仿真器来近似成本率模型。分析的结果使我们能够通过关注参数的完全信息的部分期望值来识别最重要的参数。当参数未知和部分已知时，分析确定最优解和预期相关成本。这类分析可用于确保维护计算和由此产生的建议都足够可靠。
In this paper we show how sensitivity analysis for a maintenance optimisation problem can be undertaken by using the concept of expected value of perfect information (EVPI). This concept is important in a decision-theoretic context such as the maintenance problem, as it allows us to explore the effect of parameter uncertainty on the cost and the resulting recommendations. To reduce the computational effort required for the calculation of EVPIs, we have used Gaussian process (GP) emulators to approximate the cost rate model. Results from the analysis allow us to identify the most important parameters in terms of the benefit of ’learning’ by focussing on the partial expected value of perfect information for a parameter. The analysis determines the optimal solution and the expected related cost when the parameters are unknown and partially known. This type of analysis can be used to ensure that both maintenance calculations and resulting recommendations are sufficiently robust.