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Optimization of the issuance of evacuation orders under evolving hurricane conditions

Listed author(s):
  • Yi, Wenqi
  • Nozick, Linda
  • Davidson, Rachel
  • Blanton, Brian
  • Colle, Brian
Registered author(s):

    This paper develops a bi-level programming model to optimize the issuance of evacuation orders with explicit consideration of (i) the highly uncertain evolution of the storm, and (ii) the complexity of the behavioral reaction to evolving storm conditions. A solution procedure based on progressive hedging is developed. A realistic case study for the eastern portion of the state of North Carolina is presented. Through the case study we demonstrate (1) the value of developing an evacuation order policy based on the evolution of the storm in contrast to a static policy; (2) the richness in the insights that can be provided by linking the behavioral models for evacuation decision-making with dynamic traffic assignment-based network flow models in a hurricane context; and (3) the computational promise of a progressive hedging-based solution procedure to solve large instances of the model.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0191261516305331
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    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 95 (2017)
    Issue (Month): C ()
    Pages: 285-304

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    Handle: RePEc:eee:transb:v:95:y:2017:i:c:p:285-304
    DOI: 10.1016/j.trb.2016.10.008
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    1. Xu, Kecheng & Davidson, Rachel A. & Nozick, Linda K. & Wachtendorf, Tricia & DeYoung, Sarah E., 2016. "Hurricane evacuation demand models with a focus on use for prediction in future events," Transportation Research Part A: Policy and Practice, Elsevier, vol. 87(C), pages 90-101.
    2. Ng, ManWo & Diaz, Rafael & Behr, Joshua, 2015. "Departure time choice behavior for hurricane evacuation planning: The case of the understudied medically fragile population," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 215-226.
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    6. Sherali, Hanif D. & Carter, Todd B. & Hobeika, Antoine G., 1991. "A location-allocation model and algorithm for evacuation planning under hurricane/flood conditions," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 439-452, December.
    7. Haugen, Kjetil K. & Lokketangen, Arne & Woodruff, David L., 2001. "Progressive hedging as a meta-heuristic applied to stochastic lot-sizing," European Journal of Operational Research, Elsevier, vol. 132(1), pages 116-122, July.
    8. Li, Anna C.Y. & Nozick, Linda & Xu, Ningxiong & Davidson, Rachel, 2012. "Shelter location and transportation planning under hurricane conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 715-729.
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    12. John Whitehead, 2005. "Environmental Risk and Averting Behavior: Predictive Validity of Jointly Estimated Revealed and Stated Behavior Data," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 32(3), pages 301-316, November.
    13. Bayram, Vedat & Tansel, Barbaros Ç. & Yaman, Hande, 2015. "Compromising system and user interests in shelter location and evacuation planning," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 146-163.
    14. Sheu, Jiuh-Biing & Pan, Cheng, 2014. "A method for designing centralized emergency supply network to respond to large-scale natural disasters," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 284-305.
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