Name
Abstract | ||
|---|---|---|
Kidney exchange programs enable willing, but incompatible, donor-patient pairs to swap donors, thus allowing persons suffering from organ failure to access transplantation. Choosing which pairs to match requires solving a stochastic online optimization problem where patients and donors arrive over time. Despite this, most of the related scientific literature has focused on deterministic offline models. In this paper, we present a simple approach to employ a model for the offline Kidney Exchange Problem (KEP) as the basis of an on-line anticipatory algorithm. Our approach grounds on existing techniques for the on-line KEP, but it generalizes them and provides a more accurate estimate of the expected impact of current decisions. In an experimentation based on a state-of-the-art donor pool generation method, the approach provides improvements in terms of quality and is able to deal with realistic instance size in reasonable time. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICTAI.2018.00095 | 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) |
Keywords | Field | DocType |
Optimisation,Anticipatory algorithm,Online stochastic kidney exchange | Approximation algorithm,Scientific literature,Computer science,Stochastic process,Online optimization,Artificial intelligence,Swap (finance),Transplantation,Machine learning,Scalability | Conference |
ISSN | ISBN | Citations |
1082-3409 | 978-1-5386-7450-5 | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Danuta Sorina Chisca | 1 | 1 | 1.71 |
| Michele Lombardi | 2 | 270 | 28.86 |
| Michela Milano | 3 | 1117 | 97.67 |
| barry osullivan | 4 | 74 | 17.27 |