Science of analytical reasoning
Information Visualization
IEEE Transactions on Intelligent Transportation Systems
An evacuation planner algorithm in flat time graphs
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Cell-transmission-based evacuation planning with rescue teams
Journal of Heuristics
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
An agent based model for evacuation traffic management
Proceedings of the Winter Simulation Conference
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Given a transportation network having source nodes with evacuees and destination nodes, we want to find a contraflow network configuration, i.e., ideal direction for each edge, to minimize evacuation time. Contraflow is considered a potential remedy to reduce congestion during evacuations in the context of homeland security and natural disasters (e.g., hurricanes). This problem is computationally challenging because of the very large search space and the expensive calculation of evacuation time on a given network. To our knowledge, this paper presents the first macroscopic approaches for the solution of contraflow network reconfiguration incorporating road capacity constraints, multiple sources, congestion factor, and scalability. We formally define the contraflow problem based on graph theory and provide a framework of computational workload to classify our approaches. A Greedy heuristic is designed to produce high quality solutions with significant performance. A Bottleneck Relief heuristic is developed to deal with large numbers of evacuees. We evaluate the proposed approaches both analytically and experimentally using real world datasets. Experimental results show that our contraflow approaches can reduce evacuation time by 40% or more.