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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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    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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