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Modeling Transportation Networks During Disruptions and Emergency Evacuations

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  • Shen, Zuo-Jun Max
  • Pannala, Jyothsna
  • Rai, Rohit
  • Tsoi, Tsz Shing

Abstract

The events of hurricane seasons and the threat of terrorist attacks have made evacuation during disruptions a leading management issue. Transportation networks, which form the backbone of any emergency management plan, should be able to respond to disruptions by ensuring safe, organized and quick movement of people at the time of crisis. This work proposes two models to capture the highly uncertain and time-dependent nature of transportation systems in the face of an emergency. The first model addresses the location of safety shelters. It uses risk management tools, the classical facility location model and traffic assignment techniques with Wardrop’s principle to determine the optimal location of shelters. The second model deals with real time decision-making during evacuations. It incorporates a simulation algorithm with the successive shortest path algorithm to model evacuation. Detailed traffic information in the network can be obtained from this algorithm to facilitate the evacuation.

Suggested Citation

  • Shen, Zuo-Jun Max & Pannala, Jyothsna & Rai, Rohit & Tsoi, Tsz Shing, 2008. "Modeling Transportation Networks During Disruptions and Emergency Evacuations," University of California Transportation Center, Working Papers qt1257t9zn, University of California Transportation Center.
  • Handle: RePEc:cdl:uctcwp:qt1257t9zn
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    References listed on IDEAS

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    1. 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.
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    4. Osman Alp & Erhan Erkut & Zvi Drezner, 2003. "An Efficient Genetic Algorithm for the p-Median Problem," Annals of Operations Research, Springer, vol. 122(1), pages 21-42, September.
    5. Yang, Baiyu & Miller-Hooks, Elise, 2004. "Adaptive routing considering delays due to signal operations," Transportation Research Part B: Methodological, Elsevier, vol. 38(5), pages 385-413, June.
    6. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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    Cited by:

    1. Wang, Qingyi & Wallace, Stein W., 2022. "Non-compliance in transit-based evacuation pick-up point assignments," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    2. Alizadeh, Morteza & Amiri-Aref, Mehdi & Mustafee, Navonil & Matilal, Sumohon, 2019. "A robust stochastic Casualty Collection Points location problem," European Journal of Operational Research, Elsevier, vol. 279(3), pages 965-983.
    3. Gutjahr, Walter J. & Dzubur, Nada, 2016. "Bi-objective bilevel optimization of distribution center locations considering user equilibria," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 1-22.
    4. Vedat Bayram & Hande Yaman, 2018. "Shelter Location and Evacuation Route Assignment Under Uncertainty: A Benders Decomposition Approach," Transportation Science, INFORMS, vol. 52(2), pages 416-436, March.
    5. 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.
    6. Oscar Rodríguez-Espíndola & Juan Gaytán, 2015. "Scenario-based preparedness plan for floods," 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. 76(2), pages 1241-1262, March.
    7. Suchat Tachaudomdach & Auttawit Upayokin & Nopadon Kronprasert & Kriangkrai Arunotayanun, 2021. "Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems," Sustainability, MDPI, vol. 13(6), pages 1-16, March.

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