A Data-Driven Optimization Methodology to Improve Unmatched Pairs Assignment in Kidney Exchange Problem

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Dadashi, Hossein | 2020

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 52826 (01)
University: Sharif University of Technology
Department: Industrial Engineering
Advisor(s): Najafi, Mahdi; Rafiee, Majid
Abstract:
One of the most common and effective ways to treat end-stage renal disease is the use of kidney exchange techniques. However, the main problem with this treatment is the presence of many barriers to allocating kidney pairs to each other, which reduces the success of kidney transplants. Among different types of kidney transplantation methods, the present study utilizes kidney transplantation cycles to develop the allocation of unmatched pairs in kidney transplantation using a data-driven optimization technique. In this study, HLA patients were considered as simulated and also a two-objective model in the kidney exchange network was designed to maximize the probability of kidney transplantation success and patients' waiting time weight, simultaneously. The model was also run in 4 time periods of 1-month interval and the allocation was optimized considering the patients' time weight and their chance of success in the kidney transplant pool
Keywords:
Kidney Exchange Problem ; Data Driven Method ; Optimization ; Kidney Diseases ; Human Leukocyte Antigen (HLA) ; Kidney Exchange Cycle ; Unmatched Pairs

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