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Aggregate-level demand management in evacuation planning

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

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 224 (2013)
    Issue (Month): 1 ()
    Pages: 79-92

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    Handle: RePEc:eee:ejores:v:224:y:2013:i:1:p:79-92

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Integer programming; Evacuation planning; Disaster management; Staging; Routing;

    References

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    1. Chung, Koohong & Rudjanakanoknad, Jittichai & Cassidy, Michael J., 2007. "Relation between traffic density and capacity drop at three freeway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 82-95, January.
    2. Daganzo, Carlos F., 1994. "The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory," Transportation Research Part B: Methodological, Elsevier, vol. 28(4), pages 269-287, August.
    3. Daganzo, Carlos F., 1995. "The cell transmission model, part II: Network traffic," Transportation Research Part B: Methodological, Elsevier, vol. 29(2), pages 79-93, April.
    4. Cassidy, Michael J. & Bertini, Robert L., 1999. "Some traffic features at freeway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 33(1), pages 25-42, February.
    5. Eva Regnier, 2008. "Public Evacuation Decisions and Hurricane Track Uncertainty," Management Science, INFORMS, vol. 54(1), pages 16-28, January.
    6. Urbina, Elba & Wolshon, Brian, 2003. "National review of hurricane evacuation plans and policies: a comparison and contrast of state practices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(3), pages 257-275, March.
    7. John J. Jarvis & H. Donald Ratliff, 1982. "Note---Some Equivalent Objectives for Dynamic Network Flow Problems," Management Science, INFORMS, vol. 28(1), pages 106-109, January.
    8. Tao Yao & Supreet Mandala & Byung Chung, 2009. "Evacuation Transportation Planning Under Uncertainty: A Robust Optimization Approach," Networks and Spatial Economics, Springer, vol. 9(2), pages 171-189, June.
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