2550. Computing Balanced Solutions for International Kidney Exchange Schemes
Invited abstract in session MA-11: Kidney Exchange, stream OR in Healthcare (ORAHS).
Monday, 8:30-10:00Room: Clarendon SR 1.03
Authors (first author is the speaker)
| 1. | Xin Ye
|
| 2. | Márton Benedek
|
| Corvinus University of Budapest | |
| 3. | Péter Biró
|
| Centre for Economic and Regional Studies, and Corvinus University of Budapest | |
| 4. | Gergely Csáji
|
| HUN-REN KRTK KTI | |
| 5. | Matthew Johnson
|
| Durham University | |
| 6. | Daniel Paulusma
|
| Department of Computer Science, Durham University |
Abstract
In a kidney exchange programme (KEP), patients may swap their incompatible donors leading to cycles of kidney transplants. Nowadays, to improve the total social welfare, countries may try to merge their national patient-donor pools leading to an international kidney exchange program (IKEP). To ensure fairness for participating countries in the long term while maximizing the total number of transplants, IKEPs may use a credit-based system. Such a system prescribes, in each round, a target number of kidney transplants for each country, which is determined by an initial "fair" allocation and adjusted by credits. The goal is to find, in each round, an optimal solution for the participating countries that closely approximates the target allocation. We perform large-scale simulations for IKEPs with maximum cycle lengths 2, 3 and unbounded, respectively. To obtain the initial allocations, we use six different solution concepts from cooperative game theory. In this way we are able to give a clear picture on how the stability and total social welfare of an IKEP is affected by the choice of solution concept and the maximum cycle length. This is joint work with Márton Benedek, Péter Biró, Gergely Csáji, Matthew Johnson and Daniel Paulusma.
Keywords
- Complexity and Approximation
- Algorithms
- Game Theory
Status: accepted
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