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Modeling demand management strategies for evacuations

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  • Hediye Tuydes-Yaman
  • Athanasios Ziliaskopoulos

Abstract

Evacuations are massive operations that create heavy travel demand on road networks some of which are experiencing major congestions even with regular traffic demand. Congestion in traffic networks during evacuations, can be eased either by supply or demand management actions. This study focuses on modeling demand management strategies of optimal departure time, optimal destination choice and optimal zone evacuation scheduling (also known as staggered evacuation) under a given fixed evacuation time assumption. The analytical models are developed for a system optimal dynamic traffic assignment problem, so that their characteristics can be studied to produce insights to be used for large-scale solution algorithms. While the first two strategies were represented in a linear programming (LP) model, evacuation zone scheduling problem inevitable included integers and resulted in a mixed integer LP (MILP) one. The dual of the LP produced an optimal assignment principle, and the nature of the MILP formulations revealed clues about more efficient heuristics. The discussed properties of the models are also supported via numerical results from a hypothetical network example. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Hediye Tuydes-Yaman & Athanasios Ziliaskopoulos, 2014. "Modeling demand management strategies for evacuations," Annals of Operations Research, Springer, vol. 217(1), pages 491-512, June.
  • Handle: RePEc:spr:annopr:v:217:y:2014:i:1:p:491-512:10.1007/s10479-014-1533-6
    DOI: 10.1007/s10479-014-1533-6
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    References listed on IDEAS

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    1. Lee D. Han & Fang Yuan & Shih-Miao Chin & Holing Hwang, 2006. "Global Optimization of Emergency Evacuation Assignments," Interfaces, INFORMS, vol. 36(6), pages 502-513, December.
    2. Athanasios K. Ziliaskopoulos, 2000. "A Linear Programming Model for the Single Destination System Optimum Dynamic Traffic Assignment Problem," Transportation Science, INFORMS, vol. 34(1), pages 37-49, February.
    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. 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.
    5. Xie, Chi & Lin, Dung-Ying & Travis Waller, S., 2010. "A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 295-316, May.
    6. Stepanov, Alexander & Smith, James MacGregor, 2009. "Multi-objective evacuation routing in transportation networks," European Journal of Operational Research, Elsevier, vol. 198(2), pages 435-446, October.
    7. Cova, Thomas J. & Johnson, Justin P., 2003. "A network flow model for lane-based evacuation routing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(7), pages 579-604, August.
    8. 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.
    9. Ng, ManWo & Waller, S. Travis, 2010. "Reliable evacuation planning via demand inflation and supply deflation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 1086-1094, November.
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    Cited by:

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    2. Xiaozheng He & Hong Zheng & Srinivas Peeta & Yongfu Li, 2018. "Network Design Model to Integrate Shelter Assignment with Contraflow Operations in Emergency Evacuation Planning," Networks and Spatial Economics, Springer, vol. 18(4), pages 1027-1050, December.
    3. 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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