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• We have developed a hierarchical approach to optimize evacuation management strategies under tsunami disasters. • On the first layer, the management objective is to minimize the evacuation time for all individual evacuees. • On the second layer, the optimization objective aims to minimize the total evacuation time of all the evacuees. • A heuristic solution was developed to provide coordinated vehicle routing guidance for evacuees. An optimal traffic evacuation strategy is of practical importance to minimize potential devastating damages caused by tsunamis. In this study, we developed a tsunami-induced, network-wide traffic evacuation optimization strategy. A hierarchical evacuation structure is established to guide vehicle routing decisions. At the first stage of evacuation, the optimization objective is to minimize the maximum evacuation time for all the individual evacuees from affected areas to temporary shelter zones to satisfy their primary safety needs within the shortest time periods. At the second stage of evacuation, the optimization objective aims to minimize the total evacuation time of all the evacuees from temporary shelter zones to safe zones. The lexicographic minimax optimization and Tabu search techniques are adopted to obtain a unique solution. Numerical examples are conducted to demonstrate the effectiveness of the developed model based on a real transportation network in Honolulu, Hawaii. The proposed evacuation strategy contributes to the state of the art by innovatively balancing the evacuation safety priority and the evacuation efficiency in the hierarchical evacuation structure. The research findings are helpful for decision makers to develop optimal tsunami-induced, network-wide traffic evacuation strategies. [ABSTRACT FROM AUTHOR]

• Assessing landslide-induced roadway network vulnerability and accessibility. • Vulnerability analysis is conducted by integrating static and dynamic factors. • The analytical hierarchy process model is developed to assess landslide likelihood. • A generic Vulnerability Index (VI) for each roadway link in the network. As one of the devastating natural disasters, landslide may induce significant losses of properties and lives area-wide, and generate dramatic damages to transportation network infrastructure. Accessing the impacts of landslide-induced disruptions to roadway infrastructure can be extremely difficult due to the complexity of involved impact factors and uncertainties of vulnerability related events. In this study, a data-driven approach is developed to assess landslide-induced transportation roadway network vulnerability and accessibility. The vulnerability analysis is conducted by integrating a series of static and dynamic factors to reflect the landslide likelihood and the consequences of network accessibility disruptions. The analytical hierarchy process (AHP) model was developed to assess and map the landslide likelihood. A generic vulnerability index (VI) was calculated for each roadway link in the network to identify critical links. Spatial distributions of landslide likelihood, consequences of network disruptions, and network vulnerability degrees were fused and analyzed. The roadway network on Oahu Island in Hawaii is utilized to demonstrate the effectiveness of the proposed approach with all the geo-coded information for its network vulnerability analysis induced by area-wide landslides. Specifically, the study area was classified into five categories of landslide likelihood: very high, high, moderate, low, and stable. About 34% of the study area was assigned as the high or very high categories. The results of network vulnerability analyses highlighted the importance of three highway segments tunnel through the Ko'olau Range from leeward to windward, connecting Honolulu to the windward coast including the Pali highway segment, Likelike highway segment, and Interstate H-3 highway segment. The proposed network vulnerability analysis method provides a new perspective to examine the vulnerability and accessibility of the roadway network impacted by landslides. [ABSTRACT FROM AUTHOR]