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Optimization of the issuance of evacuation orders under evolving hurricane conditions

Author

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  • Yi, Wenqi
  • Nozick, Linda
  • Davidson, Rachel
  • Blanton, Brian
  • Colle, Brian

Abstract

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.

Suggested Citation

  • Yi, Wenqi & Nozick, Linda & Davidson, Rachel & Blanton, Brian & Colle, Brian, 2017. "Optimization of the issuance of evacuation orders under evolving hurricane conditions," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 285-304.
  • 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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    References listed on IDEAS

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    5. Anyidoho, Prosper K. & Davidson, Rachel A. & Rambha, Tarun & Nozick, Linda K., 2022. "Prediction of population behavior in hurricane evacuations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 200-221.
    6. Karabuk, Suleyman & Manzour, Hasan, 2019. "A multi-stage stochastic program for evacuation management under tornado track uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 124(C), pages 128-151.
    7. Xuedong Yan & Xiaobing Liu & Yulei Song, 2018. "Optimizing evacuation efficiency under emergency with consideration of social fairness based on a cell transmission model," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-21, November.
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    9. Dian Sun & Lupeng Zhang & Zifeng Su, 2020. "Evacuate or Stay? A Typhoon Evacuation Decision Model in China Based on the Evolutionary Game Theory in Complex Networks," IJERPH, MDPI, vol. 17(3), pages 1-17, January.
    10. Rachel A. Davidson & Linda K. Nozick & Tricia Wachtendorf & Brian Blanton & Brian Colle & Randall L. Kolar & Sarah DeYoung & Kendra M. Dresback & Wenqi Yi & Kun Yang & Nicholas Leonardo, 2020. "An Integrated Scenario Ensemble‐Based Framework for Hurricane Evacuation Modeling: Part 1—Decision Support System," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 97-116, January.
    11. Esposito Amideo, A. & Scaparra, M.P. & Kotiadis, K., 2019. "Optimising shelter location and evacuation routing operations: The critical issues," European Journal of Operational Research, Elsevier, vol. 279(2), pages 279-295.
    12. Wu, Lingxiao & Yang, Dong & Wang, Shuaian & Yuan, Yun, 2020. "Evacuating offshore working barges from a land reclamation site in storm emergencies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
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    14. Kun Yang & Rachel A. Davidson & Humberto Vergara & Randall L. Kolar & Kendra M. Dresback & Brian A. Colle & Brian Blanton & Tricia Wachtendorf & Jennifer Trivedi & Linda K. Nozick, 2019. "Incorporating inland flooding into hurricane evacuation decision support modeling," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 96(2), pages 857-878, March.
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    16. Urena Serulle, Nayel & Cirillo, Cinzia, 2017. "The optimal time to evacuate: A behavioral dynamic model on Louisiana resident data," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 447-463.

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