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An integer L-shaped algorithm for the integrated location and network restoration problem in disaster relief

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  • Sanci, Ece
  • Daskin, Mark S.

Abstract

Being prepared for potential disaster scenarios enables government agencies and humanitarian organizations to respond effectively once the disaster hits. In the literature, two-stage stochastic programming models are commonly employed to develop preparedness plans before anticipated disasters. These models can be very difficult to solve as the complexity increases with several sources of uncertainty and interdependent decisions. In this study, we propose an integer L-shaped algorithm to solve the integrated location and network restoration model, which is a two-stage stochastic programming model determining the number and locations of the emergency response facilities and restoration resources under uncertainty. Our algorithm accommodates the second-stage binary decision variables which are required to indicate undamaged and restored roads of the network that can be used for relief distribution. Our computational results show that our algorithm outperforms CPLEX for the larger number of disaster scenarios as the solution time of our algorithm increases only linearly as the number of scenarios increases.

Suggested Citation

  • Sanci, Ece & Daskin, Mark S., 2021. "An integer L-shaped algorithm for the integrated location and network restoration problem in disaster relief," Transportation Research Part B: Methodological, Elsevier, vol. 145(C), pages 152-184.
    • Handle: RePEc:eee:transb:v:145:y:2021:i:c:p:152-184
    DOI: 10.1016/j.trb.2021.01.005
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    Citations

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    Cited by:

    1. Liu, Baoli & Li, Zhi-Chun & Wang, Yadong, 2022. "A two-stage stochastic programming model for seaport berth and channel planning with uncertainties in ship arrival and handling times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    2. Liu, Kanglin & Yang, Liu & Zhao, Yejia & Zhang, Zhi-Hai, 2023. "Multi-period stochastic programming for relief delivery considering evolving transportation network and temporary facility relocation/closure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    3. Yu, Wuyang, 2023. "A robust model for emergency supplies prepositioning and transportation considering road disruptions," Operations Research Perspectives, Elsevier, vol. 10(C).
    4. Guillot, Matthieu & Rey, David & Furno, Angelo & El Faouzi, Nour-Eddin, 2024. "A stochastic hub location and fleet assignment problem for the design of reconfigurable park-and-ride systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    5. Souza Almeida, Luana & Goerlandt, Floris & Pelot, Ronald, 2022. "Trends and gaps in the literature of road network repair and restoration in the context of disaster response operations," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    6. Hosseini, Yaser & Mohammadi, Reza Karami & Yang, Tony Y., 2024. "A comprehensive approach in post-earthquake blockage prediction of urban road network and emergency resilience optimization," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    7. Zhang, Yuwei & Li, Zhenping & Zhao, Yuwei, 2023. "Multi-mitigation strategies in medical supplies for epidemic outbreaks," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    8. Wang, Qingyi & Liu, Zhuomeng & Jiang, Peng & Luo, Li, 2022. "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).

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