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Organ transportation and allocation problem under medical uncertainty: A real case study of liver transplantation

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  • Kargar, Bahareh
  • Pishvaee, Mir Saman
  • Jahani, Hamed
  • Sheu, Jiuh-Biing

Abstract

Organ allocation is the most important decision amongst organ transplantation decisions thanks to the high demand of organs. This research develops a possibilistic programming model for a liver transportation and allocation problem considering medical uncertainty and tradeoff between quality metrics, namely efficiency and equity. The model maximizes the survival rate of patients and minimizes the transportation cost and time. A novel hybrid interactive fuzzy optimization model is developed based on preemptive goal programming approach. Several numerical examples are taken from a real case study. The results demonstrate that the suggested algorithm outperforms the existing allocation policy, considering both metrics.

Suggested Citation

  • Kargar, Bahareh & Pishvaee, Mir Saman & Jahani, Hamed & Sheu, Jiuh-Biing, 2020. "Organ transportation and allocation problem under medical uncertainty: A real case study of liver transplantation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
  • Handle: RePEc:eee:transe:v:134:y:2020:i:c:s1366554519309408
    DOI: 10.1016/j.tre.2020.101841
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    Cited by:

    1. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    2. Jahani, Hamed & Chaleshtori, Amir Eshaghi & Khaksar, Seyed Mohammad Sadegh & Aghaie, Abdollah & Sheu, Jiuh-Biing, 2022. "COVID-19 vaccine distribution planning using a congested queuing system—A real case from Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).

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