Robust Dynamic Optimization with Application to Kidney Exchange (Doctoral Consortium)

13th International Conference on Autonomous Agents and Multiagent Systems

John P. Dickerson

PID  :  119517

来源: CEUR

【 摘 要 】

Kidney exchange provides a lifesaving alternative to long waiting lists for patients in need of a new kidney. We derive a variety of mathematical models for the kidney exchange optimization prob lem, where the general goal is to maximize some form of social welfare visvis transplanting kidneys. We explore the implica tions of making the optimization problem dynamic (considering the future evolution of the exchange pool when optimizing now), failureaware (where possible postalgorithmic match failures are accounted for), and fairnessaware (losing overall efficiency at the cost of a more balanced matching). Our goal is to provide an empir ically grounded framework that combines each of these dimensions in a theoretically sound way. We support our models with real re