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Robust scheduling for large scale evacuation planning

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  • Lakshay,
  • Bolia, Nomesh B.

Abstract

It is crucial to develop appropriate strategies to reduce the evacuation time in a disaster situation. The negative impact of large scale disasters can be mitigated by proactive and efficient (time optimal) evacuation planning. The present study aims to develop strategies for public transit-based evacuation for better control and reduced congestion. Mathematical models are formulated for both strategic and operational aspects of evacuation planning to result in efficient, optimal evacuation. The study also presents methods to manage the external environment uncertainties, in particular, evacuation demand uncertainty, by providing robust solutions. To test the efficacy of the models, a case study for a radiological accident in a nuclear plant in India is presented. The results of the case study demonstrate that the models can provide live, efficient and robust results during actual emergencies in acceptable time.

Suggested Citation

  • Lakshay, & Bolia, Nomesh B., 2020. "Robust scheduling for large scale evacuation planning," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:soceps:v:71:y:2020:i:c:s0038012118301472
    DOI: 10.1016/j.seps.2019.100756
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    References listed on IDEAS

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    1. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    2. Roy, Debjit & Anuj Sharma & Ashish Kumar & Vivek Saurabh, 2014. "Location Identification for Rapid Evacuation from a Disaster Site: A Case Study from KAPS," IIMA Working Papers WP2014-09-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. Bhatnagar, Abhishek & Bolia, Nomesh B., 2019. "Improved governance of Indian school system through school consolidation," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1160-1178.
    4. Daoliang, Zhao & Lizhong, Yang & Jian, Li, 2006. "Exit dynamics of occupant evacuation in an emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 501-511.
    5. 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.
    6. Goerigk, Marc & Deghdak, Kaouthar & T’Kindt, Vincent, 2015. "A two-stage robustness approach to evacuation planning with buses," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 66-82.
    7. Fanwen Meng & Jin Qi & Meilin Zhang & James Ang & Singfat Chu & Melvyn Sim, 2015. "A Robust Optimization Model for Managing Elective Admission in a Public Hospital," Operations Research, INFORMS, vol. 63(6), pages 1452-1467, December.
    8. Suman, Hemant K. & Bolia, Nomesh B., 2019. "Improvement in direct bus services through route planning," Transport Policy, Elsevier, vol. 81(C), pages 263-274.
    9. Debjit Roy & Anuj Sharma, 2014. "Location Identification for Rapid Evacuation from a Disaster Site: A Case Study from KAPS," Working Papers id:6225, eSocialSciences.
    10. 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.
    11. Eliahu Stern & Zila Sinuany‐Stern, 1989. "A Behavioural‐Based Simulation Model For Urban Evacuation," Papers in Regional Science, Wiley Blackwell, vol. 66(1), pages 87-103, January.
    12. Joel Goh & Melvyn Sim, 2011. "Robust Optimization Made Easy with ROME," Operations Research, INFORMS, vol. 59(4), pages 973-985, August.
    13. Gorissen, Bram L. & Yanıkoğlu, İhsan & den Hertog, Dick, 2015. "A practical guide to robust optimization," Omega, Elsevier, vol. 53(C), pages 124-137.
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    Cited by:

    1. Liu, Enze & Barker, Kash & Chen, Hong, 2022. "A multi-modal evacuation-based response strategy for mitigating disruption in an intercity railway system," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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