Efficient algorithms for finding maximum matching in graphs
ACM Computing Surveys (CSUR)
Clearing algorithms for barter exchange markets: enabling nationwide kidney exchanges
Proceedings of the 8th ACM conference on Electronic commerce
Proceedings of the 11th ACM conference on Electronic commerce
Individual rationality and participation in large scale, multi-hospital kidney exchange
Proceedings of the 12th ACM conference on Electronic commerce
An improved 2-agent kidney exchange mechanism
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
Optimizing kidney exchange with transplant chains: theory and reality
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Paired and altruistic kidney donation in the UK: algorithms and experimentation
SEA'12 Proceedings of the 11th international conference on Experimental Algorithms
Harnessing the power of two crossmatches
Proceedings of the fourteenth ACM conference on Electronic commerce
Proceedings of the fourteenth ACM conference on Electronic commerce
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In kidney exchanges, hospitals share patient lists and receive transplantations. A kidney-paired donation (KPD) mechanism needs to promote full sharing of information about donor-patient pairs, and identify a Pareto efficient outcome that also satisfies participation constraints of hospitals. We introduce a random graph model of the KPD exchange and then fully characterize the structure of the efficient outcome and the expected number of transplantations that can be performed. Random graph theory allows early experimental results to be explained analytically, and enables the study of participation incentives in a methodological way. We derive a square-root law between the welfare gains from sharing patient-donor pairs in a central pool and the individual sizes of hospitals, illustrating the urgent need for the nationwide expansion of such programs. Finally, we establish through theoretical and computational analysis that enforcing simple individual rationality constraints on the outcome can mitigate the negative impact of strategic behavior by hospitals.