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Integrated design of emergency shelter and medical networks considering diurnal population shifts in urban areas

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  • Qing-Mi Hu
  • Laijun Zhao
  • Huiyong Li
  • Rongbing Huang

Abstract

This article addresses an emergency shelter and medical network design problem by integrating evacuation and medical service activities and considering diurnal population shifts to respond to large-scale natural disasters in urban areas. A multi-objective mixed-integer programming model that incorporates the characteristics of diurnal population shifts is developed to determine the configuration of the integrated emergency shelter and medical network. An accelerated Benders decomposition algorithm is then devised to solve large-scale problems in reasonable time. A realistic case study on the Xuhui District of Shanghai City in China and extensive numerical experiments are presented to demonstrate the effectiveness of the proposed model and solution method. Computational results suggest that more emergency shelters and emergency medical centers should be established when accounting for diurnal population shifts than when diurnal population shifts are not considered. The accelerated Benders decomposition algorithm is significantly more time efficient as compared with the CPLEX solver.

Suggested Citation

  • Qing-Mi Hu & Laijun Zhao & Huiyong Li & Rongbing Huang, 2019. "Integrated design of emergency shelter and medical networks considering diurnal population shifts in urban areas," IISE Transactions, Taylor & Francis Journals, vol. 51(6), pages 614-637, June.
    • Handle: RePEc:taf:uiiexx:v:51:y:2019:i:6:p:614-637
    DOI: 10.1080/24725854.2018.1519744
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    Cited by:

    1. Sun, Huali & Li, Jiamei & Wang, Tingsong & Xue, Yaofeng, 2022. "A novel scenario-based robust bi-objective optimization model for humanitarian logistics network under risk of disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).

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