Organ transportation and allocation problem under medical uncertainty: A real case study of liver transplantation
Mir Saman Pishvaee,
Hamed Jahani and
Transportation Research Part E: Logistics and Transportation Review, 2020, vol. 134, issue C
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.
Keywords: Organ transplantation; Organ transportation network; Fuzzy sets; Possibilistic programming; Preemptive goal programming (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:transe:v:134:y:2020:i:c:s1366554519309408
Ordering information: This journal article can be ordered from
http://www.elsevier. ... 600244/bibliographic
Access Statistics for this article
Transportation Research Part E: Logistics and Transportation Review is currently edited by W. Talley
More articles in Transportation Research Part E: Logistics and Transportation Review from Elsevier
Bibliographic data for series maintained by Catherine Liu ().