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We consider a well-studied online random graph model for kidney exchange, where nodes representing patient-donor pairs arrive over time, and the probability of a directed edge is p. We assume existence of a single altruistic donor, who serves as a start node in this graph for a directed path of donations. The algorithmic problem is to select which donations to perform, and when, to minimize the amount of time that patients must wait before receiving a kidney. We advance our understanding of this setting by (1) providing efficient (in fact, linear-time) algorithms with optimal O(1/p) expected waiting time, (2) showing that some of these algorithms in fact provide guarantees to all patients of O(1/p) waiting time {em with high probability}, (3) simplifying previous analysis of this problem, and (4) extending results to the case of multiple altruistic donors.
Algorithms for exchange of kidneys is one of the key successful applications in market design, artificial intelligence, and operations research. Potent immunosuppressant drugs suppress the bodys ability to reject a transplanted organ up to the point
To overcome incompatibility issues, kidney patients may swap their donors. In international kidney exchange programmes (IKEPs), countries merge their national patient-donor pools. We consider a recent credit system where in each round, countries are
Motivated by kidney exchange, we study the following mechanism-design problem: On a directed graph (of transplant compatibilities among patient-donor pairs), the mechanism must select a simple path (a chain of transplantations) starting at a distingu
In barter exchanges, participants directly trade their endowed goods in a constrained economic setting without money. Transactions in barter exchanges are often facilitated via a central clearinghouse that must match participants even in the face of
Current kidney exchange pools are of moderate size and thin, as they consist of many highly sensitized patients. Creating a thicker pool can be done by waiting for many pairs to arrive. We analyze a simple class of matching algorithms that search per