Highlights A possibilistic programming approach is proposed for a liver transportation and allocation. The proposed model considers medical uncertainty as well as tradeoff between quality metrics in organ transplantation. The model aims to maximize the survival rate, deliberating the most urgent need for liver transplantation, and minimize the transportation cost and time. A novel interactive fuzzy optimization model is developed based on goal programming approach. The numerical results demonstrate that the suggested algorithm outperforms the existing allocation policy, efficiency and equity metrics.

    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.


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    Titel :

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


    Beteiligte:


    Erscheinungsdatum :

    2020-01-09




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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