Highlights Systematic identification of values in road network disaster recovery context. A model-driven set of six DRPTN decision attributes. Practical implications and key remarks for DRR decision-makers and research. Maximizing efficacy and efficiency of recovery, network's mobility and accessibility.

    Abstract This paper implements a structured framework to suggest decision attributes of transportation network disaster recovery planning. For this purpose, we collected 57 decision attributes from the relevant literature and experts’ opinions. Following a framework with three sequential evaluation stages, decision-makers systematically assessed the attributes based on each evaluation stage’s specific criteria. Thereafter, we aggregated the decision-makers’ input values using a combination of compensatory and non-compensatory Multi-Attribute Decision-Making techniques. Results offer a ranked list of attributes and a recommended set of attributes for Tehran’s road network as our case study. The findings suggest six attributes to be included in road network disaster recovery planning as 1) access level to service-providing nodes, 2) integration of link travel delay and traffic flow, 3) travel time improvement per recovery duration, 4) travel time improvement per resources, 5) centrality measures, and 6) link capacity. However, the recommended attributes are valid only when they remain as a set. Results contribute to the existing knowledge about concerns and values in the reconstruction and recovery of transportation networks after disasters. Transportation network planners and disaster managers can use the recommended attributes as key factors for post-disaster decision support systems or for evaluating available disaster resiliency plans. Additionally, future research can adopt this research outcome as an input for the problem-structuring phase of disaster recovery models.


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    Title :

    Decision attributes for disaster recovery planning of transportation networks; A case study


    Contributors:


    Publication date :

    2021-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English