Kidney exchange programs (KEPs) form an innovative approach to increasing the donor pool through allowing the participation of renal patients together with a willing but incompatible donor. The aim of a KEP is to identify groups of incompatible donor-recipient pairs that could exchange donors leading to feasible transplants. As the size of a kidney exchange grows, a larger proportion of participants can be transplanted. Collaboration between multiple transplant centers, by merging their separate kidney exchange pools is thus desirable. As each transplant center has its own interest to provide the best care to its own patients, collaboration requires balancing individual and common objectives. We consider a class of algorithmic mechanisms for multi-center kidney exchange programs we call rejection-proof mechanisms. Such mechanisms propose solutions with the property that no player wishes to unilaterally deviate. We provide a mechanism optimizing social value under this restriction, though the underlying optimization problem is Sigma-2-p-Hard. We also describe a computationally easier but sub-optimal alternative. Experiments show that rejection-proofness can be achieved at limited cost compared to optimal solutions for regular kidney exchange. Computationally, we provide algorithms to compute optimal rejection-proof solutions for small and medium instance sizes.
翻译:肾交换方案(KEPs)通过允许肾病患者与愿意但互不相容的捐赠者共同参与,形成一种创新的方法来增加捐赠者的资金库。KEP的目的是确定不相容的捐赠者-接受者对等群体,以交换捐赠者,从而实现可行的移植。随着肾交换规模的扩大,更多的参与者可以移植。因此,多移植中心之间通过合并其独立的肾交换池进行协作是可取的。由于每个移植中心都有自己的利益为自己的病人提供最好的护理,因此合作需要平衡个人和共同目标。我们认为,多中枢肾交换方案有一类算法机制,我们称之为防止拒绝机制。这种机制提出解决方案的属性,没有任何参与者希望单方面偏离。我们提供了一个机制,在这种限制下优化社会价值的优化机制,尽管潜在的优化问题是Sigma-2p-Hard。我们还描述了一种比较容易计算、但又次优化的替代方案。实验表明,与定期肾交换的最佳解决方案相比,可以以有限的成本实现拒绝。比较,我们提供了一种算法,我们为中小和中小体大小的最佳抵制解决方案提供了最优的算法。