Kargar, B.B.KargarPishvaee, M.S.M.S.PishvaeeJahani, H.H.JahaniJIUH-BIING SHEU2020-12-112020-12-112020https://www.scopus.com/inward/record.url?eid=2-s2.0-85078560355&partnerID=40&md5=44a9c07c72a78c28b94238209a54481ehttps://scholars.lib.ntu.edu.tw/handle/123456789/525347Organ 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. ? 2020 Elsevier LtdFuzzy sets; Organ transplantation; Organ transportation network; Possibilistic programming; Preemptive goal programming[SDGs]SDG3algorithm; fuzzy mathematics; logistics; numerical model; optimization; public health; uncertainty analysisjournal article10.1016/j.tre.2020.101841WOS:0005184896000082-s2.0-85078560355WOS:000518489600008