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Aggregate-level demand management in evacuation planning

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  • Bish, Douglas R.
  • Sherali, Hanif D.

Abstract

Without successful large-scale regional evacuations, threats such as hurricanes and wild-fires can cause a large loss of life. In this context, automobiles are oftentimes an essential transportation mode for evacuations, but the ensuing traffic typically overwhelms the roadway capacity and causes congestion on a massive scale. Congestion leads to many problems including longer, costlier, and more stressful evacuations, lower compliance rates, and increased risk to the population. Supply-based strategies have traditionally been used in evacuation planning, but they have been proven to be insufficient to reduce congestion to acceptable levels. In this paper, we study the demand-based strategies of aggregate-level staging and routing to structure the evacuation demand, both with and without congestion. We provide a novel modeling framework that offers strategic flexibility and utilizes a lexicographic objective function that represents a hierarchy of relevant evacuation-based goals. We also provide insights into the nature and effect of network bottlenecks. We compare our model with and without congestion in relation to tractability, normative optimality, and robustness under demand uncertainty. We also show the effectiveness of using demand-based strategies as opposed to using the status quo that involves a non-staged or simultaneous evacuation process. Effective solution procedures are developed and tested using hypothetical problem instances as well as using a larger study based on a portion of coastal Virginia, USA.

Suggested Citation

  • Bish, Douglas R. & Sherali, Hanif D., 2013. "Aggregate-level demand management in evacuation planning," European Journal of Operational Research, Elsevier, vol. 224(1), pages 79-92.
  • Handle: RePEc:eee:ejores:v:224:y:2013:i:1:p:79-92
    DOI: 10.1016/j.ejor.2012.07.036
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    3. Lv, Y. & Yan, X.D. & Sun, W. & Gao, Z.Y., 2015. "A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 188-199.
    4. Afkham, Maryam & Ramezanian, Reza & Shahparvari, Shahrooz, 2022. "Balancing traffic flow in the congested mass self-evacuation dynamic network under tight preparation budget: An Australian bushfire practice," Omega, Elsevier, vol. 111(C).
    5. Rambha, Tarun & Nozick, Linda K. & Davidson, Rachel & Yi, Wenqi & Yang, Kun, 2021. "A stochastic optimization model for staged hospital evacuation during hurricanes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
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    7. Praveen Maghelal & Xiangyu Li & Walter Gillis Peacock, 2017. "Highway congestion during evacuation: examining the household’s choice of number of vehicles to evacuate," 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. 87(3), pages 1399-1411, July.
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    11. Melissa Gama & Bruno Filipe Santos & Maria Paola Scaparra, 2016. "A multi-period shelter location-allocation model with evacuation orders for flood disasters," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 299-323, September.
    12. Rodríguez-Espíndola, Oscar & Albores, Pavel & Brewster, Christopher, 2018. "Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods," European Journal of Operational Research, Elsevier, vol. 264(3), pages 978-993.
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    14. Bian Liang & Dapeng Yang & Xinghong Qin & Teresa Tinta, 2019. "A Risk-Averse Shelter Location and Evacuation Routing Assignment Problem in an Uncertain Environment," IJERPH, MDPI, vol. 16(20), pages 1-28, October.
    15. Jiang-Hua Zhang & Hai-Yue Liu & Rui Zhu & Yang Liu, 2017. "Emergency Evacuation of Hazardous Chemical Accidents Based on Diffusion Simulation," Complexity, Hindawi, vol. 2017, pages 1-16, December.
    16. Zhao-ge Liu & Xiang-yang Li & Dilawar Khan Durrani, 2021. "Generating evacuation task plans for community typhoon emergencies: an integration of case-driven and model-driven approaches," Operational Research, Springer, vol. 21(1), pages 745-774, March.
    17. Shahparvari, Shahrooz & Chhetri, Prem & Abbasi, Babak & Abareshi, Ahmad, 2016. "Enhancing emergency evacuation response of late evacuees: Revisiting the case of Australian Black Saturday bushfire," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 148-176.
    18. 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.
    19. Bayram, Vedat & Yaman, Hande, 2024. "A joint demand and supply management approach to large scale urban evacuation planning: Evacuate or shelter-in-place, staging and dynamic resource allocation," European Journal of Operational Research, Elsevier, vol. 313(1), pages 171-191.
    20. Zixin Zhang & Liang Wang & Jiayan Lai & Yingming Wang, 2023. "A Dynamic Emergency Plan Generation Method Considering Different Situations and Limited Resources," Sustainability, MDPI, vol. 15(7), pages 1-11, March.
    21. Kimms, A. & Maiwald, M., 2018. "Bi-objective safe and resilient urban evacuation planning," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1122-1136.
    22. 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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