Prioritization of highway maintenance functions using multi-attribute decision making with fuzzy pairwise comparison
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As is the case for most of the Departments of Transportation in the U.S., the Texas Department of Transportation has been experiencing fluctuations of budget for maintaining and preserving its highway infrastructure over the recent years. If the maintenance budget shortfall lasts for an extended period of time, the condition of the highway network would be harmed directly or indirectly since some maintenance work would be deferred or cancelled. Thus, in order to control and minimize the risk caused by maintenance budget reductions, it is important for highway agencies to adjust their maintenance and rehabilitation policies to accommodate budget fluctuations. This thesis presents a methodological framework that helps highway agencies quantify the risks to highway networks, and revise the highway routine maintenance work plans to minimize the impact of budget fluctuations. The proposed methodology aims to assist highway agencies in prioritizing and selecting maintenance functions according to the risk of not performing a specific maintenance activity. Also, this methodology considers the subjective nature of decision makers’ assessments, allowing different levels of confidence and different attitudes toward risk to be captured as the uncertainty and imprecision involved in the decision making process. In the case study, the proposed methodology is tested with a set of data obtained from the Texas Department of Transportation. The result is compared with the outcome obtained from the crisp Analytical Hierarchy Process using the same set of data. The outcomes from the two methodologies are very close, validating the effectiveness of prioritizing highway maintenance functions using Multi-Attribute Analysis with Fuzzy Pairwise Comparison.