Date of Award

August 2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Industrial Engineering

Committee Member

Amin Khademi

Committee Member

Burak Eksioglu

Committee Member

Cole J Smith

Committee Member

Kevin M Taaffe

Abstract

In this dissertation, we utilize several mathematical, optimization, and simulation techniques to improve the outcomes of organ transplantation allocation systems. Specifically, in Chapter 1, we build a Monte Carlo simulation model of the heart transplantation system in the United States that can be used to compare the performance of different allocation policies and predict the future of allocation systems. In Chapter 2, we develop a constrained Markov Decision model of the transplant queuing system and investigate optimal allocation rules for heart transplantation in the presence of certain fairness constraints. In Chapter 3, we introduce a new measure of fairness in the organ transplantation queuing systems. We show that this measure helps improve the performance loss of incorporating fairness considerations in organ transplantation systems, and decrease the price of fairness.

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