Optimal infrastructure management decisions under uncertainty
Optimal infrastructure management decisions under uncertainty
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DOI：
10.1016/0968-090x(93)90021-7
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发表时间：
1993-03
影响因子：
8.3
通讯作者：
S. Madanat
中科院分区：
文献类型：
--
作者：
S. Madanat
运输设施维修和修复活动的规划使用来自两个来源的设施状况信息：测量和预测。这两种来源的特点是存在很大的不确定性，这对生命周期成本有重要影响。最先进的决策模型忽略了一个或两个信息来源的不确定性。本文提出了一种方法（隐马尔可夫决策过程），明确地识别随机测量误差的存在的设施状态的测量。该方法还可用于量化“更精确信息的价值”，使机构能够评估不同精度和成本的测量技术。一个参数研究，证明了这样的评价在公路路面的情况下，进行了。
The planning of maintenance and rehabilitation activities for transportation facilities uses information on facility condition from two sources: measurement and forecasting. Both of these sources are characterized by the presence of significant uncertainties, which have important life-cycle cost implications. State-of-the-art decision-making models ignore the uncertainty either in one or both sources of information. This paper presents a methodology (the Latent Markov Decision Process) that explicitly recognizes the presence of random measurement errors in the measurement of facility condition. The methodology can also be used to quantify the “value of more precise information,” which allows an agency to evaluate measurement technologies of different precisions and costs. A parametric study, which demonstrates such an evaluation in the case of highway pavements, is performed.