Transportation infrastructure connects people and businesses with each other and the rest of the world. It is vital to economy and social well-being of people. Unfortunately, due to system age and lack of maintenance and modernization activities, the condition of the transportation infrastructure is degrading and availability is decreasing. This degradation is compounded when coupled with the growing backlog of needs and limited resources, making prioritization of these activities a complex problem. Current transportation infrastructure maintenance and modernization management practices prioritize resource needs based on a “worst first” basis and prepare short-term plans. In order to prepare long-term plans, all factors must be considered. Therefore, a systems thinking approach using a comprehensive multi-criteria decision-making framework should be adopted when making infrastructure maintenance and modernization decisions. The frameworks offered in academia for maintenance and modernization decision-making lack a holistic approach, objectivity and topological aspect. To address shortcomings, this research proposes a new comprehensive decision-making framework for maintenance and modernization of aging transportation infrastructure. The framework includes four stages. The first stage employees a systems thinking approach to frame the problem and identify impact factors. The second stage conducts complex network analysis to assess the location criticality of each component within the transportation infrastructure network. The third stage is data collection and preprocessing, in which agency reports are reviewed to identify available data. The fourth and the final stage, constructs a Bayesian network model using real-world data without subjective judgement. At this stage, after the structure and parameters are learned, component specific data (evidence) is entered, and a maintenance and modernization index (M&M; Index) number is obtained per component. The robustness of the proposed framework is demonstrated using a case study for inland waterways. This transportation structure was chosen because it has not been analyzed holistically using a multi-criteria decision-making framework. The results confirm that the prioritization determined by utilizing the proposed framework optimizes system availability. This new framework provides decision makers with a M&M; Index number representing the prioritized need for maintenance and modernization of each project.
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