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A logistics model for the transport of disaster victims with various injuries and survival probabilities

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  • Sukho Jin
  • Sukjae Jeong
  • Jangyeop Kim
  • Kyungsup Kim

Abstract

We propose an optimization model for patient delivery and medical resource allocation with capacity restrictions. Our model considers the severity of the victims’ injuries in the initial search and rescue period and their survival probabilities, which decrease proportionally with the elapsed time. We develop a mixed integer programming model to select the location and network flow of an on-site clinic for supporting first-aid treatment near disaster areas. We also build a model of a general hospital as an objective function to maximize the number of patients whose survival probability exceeds the marginal level. Our model also considers patients waiting at the on-site clinic and hospital. We apply our optimization approach in a case study with data from a department store collapse in South Korea. Our computational results will facilitate future studies of logistics to support wounded victims of disasters. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Sukho Jin & Sukjae Jeong & Jangyeop Kim & Kyungsup Kim, 2015. "A logistics model for the transport of disaster victims with various injuries and survival probabilities," Annals of Operations Research, Springer, vol. 230(1), pages 17-33, July.
    • Handle: RePEc:spr:annopr:v:230:y:2015:i:1:p:17-33:10.1007/s10479-013-1515-0
    DOI: 10.1007/s10479-013-1515-0
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    References listed on IDEAS

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    Cited by:

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    9. Rezapour, Shabnam & Naderi, Nazanin & Morshedlou, Nazanin & Rezapourbehnagh, Shaghayegh, 2018. "Optimal deployment of emergency resources in sudden onset disasters," International Journal of Production Economics, Elsevier, vol. 204(C), pages 365-382.
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    13. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency Relief Routing Models for Injured Victims Considering Equity and Priority," Post-Print hal-02879681, HAL.
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    15. Hanif Malekpoor & Konstantinos Chalvatzis & Nishikant Mishra & Amar Ramudhin, 2019. "A hybrid approach of VIKOR and bi-objective integer linear programming for electrification planning in a disaster relief camp," Annals of Operations Research, Springer, vol. 283(1), pages 443-469, December.
    16. Diaz, Rafael & Behr, Joshua G. & Acero, Beatriz, 2022. "Coastal housing recovery in a postdisaster environment: A supply chain perspective," International Journal of Production Economics, Elsevier, vol. 247(C).
    17. Junhu Ruan & Felix T. S. Chan & Xiaofeng Zhao, 2018. "Re-Planning the Intermodal Transportation of Emergency Medical Supplies with Updated Transfer Centers," Sustainability, MDPI, vol. 10(8), pages 1-20, August.
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    19. Abhijit Baidya & Uttam Kumar Bera, 2019. "New model for addressing supply chain and transport safety for disaster relief operations," Annals of Operations Research, Springer, vol. 283(1), pages 33-69, December.
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    21. Kamyabniya, Afshin & Noormohammadzadeh, Zohre & Sauré, Antoine & Patrick, Jonathan, 2021. "A robust integrated logistics model for age-based multi-group platelets in disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    22. Pravin Kumar & Rajesh Kr Singh, 2022. "Application of Industry 4.0 technologies for effective coordination in humanitarian supply chains: a strategic approach," Annals of Operations Research, Springer, vol. 319(1), pages 379-411, December.
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    24. Hasti Seraji & Reza Tavakkoli-Moghaddam & Sobhan Asian & Harpreet Kaur, 2022. "An integrative location-allocation model for humanitarian logistics with distributive injustice and dissatisfaction under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 211-257, December.

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