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Evacuation Planning with Endogenous Transportation Network Degradations: A Stochastic Cell-Based Model and Solution Procedure

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  • Jian Li
  • Kaan Ozbay

Abstract

Capturing the impact of uncertain events in emergency evacuation time estimation is an important issue for public officials to avoid unexpected delays and related losses of life and property. However, most of the current studies in evacuation planning only focus on exogenous uncertainties, such as flooding damage in a hurricane, but ignore uncertainties caused by endogenously determined risks, or so called flow-related risks. This paper proposes an analytical framework along with an efficient solution methodology to evaluate the impact of endogenously determined risks in order to estimate evacuation time. We incorporate the probability function of endogenously determined risks in a cell-based macroscopic evacuation model. A network flow algorithm based on the sample average approximation approach is used as part of the solution procedure. Finally, a sample network is used to demonstrate the salient features of the proposed stochastic model and solution procedure. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Jian Li & Kaan Ozbay, 2015. "Evacuation Planning with Endogenous Transportation Network Degradations: A Stochastic Cell-Based Model and Solution Procedure," Networks and Spatial Economics, Springer, vol. 15(3), pages 677-696, September.
    • Handle: RePEc:kap:netspa:v:15:y:2015:i:3:p:677-696
    DOI: 10.1007/s11067-014-9241-y
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    References listed on IDEAS

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    Cited by:

    1. Laure Rousset & César Ducruet, 2020. "Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns," Post-Print halshs-02588551, HAL.
    2. MD Jahedul Alam & Muhammad Ahsanul Habib, 2021. "Mass evacuation microsimulation modeling considering traffic disruptions," 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. 108(1), pages 323-346, August.
    3. Piyapong Suwanno & Chaiwat Yaibok & Noriyasu Tsumita & Atsushi Fukuda & Kestsirin Theerathitichaipa & Manlika Seefong & Sajjakaj Jomnonkwao & Rattanaporn Kasemsri, 2023. "Estimation of the Evacuation Time According to Different Flood Depths," Sustainability, MDPI, vol. 15(7), pages 1-23, April.
    4. Laure Rousset & César Ducruet, 2020. "Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns," Networks and Spatial Economics, Springer, vol. 20(2), pages 423-447, June.
    5. 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.
    6. 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.
    7. David S. Dixon & Pallab Mozumder & William F. Vásquez & Hugh Gladwin, 2017. "Heterogeneity Within and Across Households in Hurricane Evacuation Response," Networks and Spatial Economics, Springer, vol. 17(2), pages 645-680, June.
    8. 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.

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