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arXiv 2103.02253cs.GTcs.DS
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使用免疫抑制剂的最佳肾脏交换

Optimal Kidney Exchange with Immunosuppressants

Haris Aziz, Agnes Cseh, John P. Dickerson, Duncan C. McElfresh

摘要:

肾脏交换算法是市场设计、人工智能和运筹学中的关键成功应用之一。有效的免疫抑制药物抑制身体排斥移植器官的能力,直到有可能进行血液或组织类型不相容的移植。与标准的肾脏交换问题相反,我们考虑的设置,也涉及决定哪些收件人从有限的免疫抑制剂供应,使他们与原来不兼容的肾脏兼容。我们首先提出了一个通用的计算框架来模拟这个问题。我们的主要贡献是一系列有效的算法,提供灵活性,在满足有意义的目标。出于当前现实的肾脏交换使用复杂的基于并行编程的清除算法,然后,我们提出了一个通用的,但可扩展的方法,以最佳的清除与免疫抑制,我们验证了我们的方法从一个大的实地交流的现实数据。

英文摘要:

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 body's ability to reject a transplanted organ up to the point that a transplant across blood- or tissue-type incompatibility becomes possible. In contrast to the standard kidney exchange problem, we consider a setting that also involves the decision about which recipients receive from the limited supply of immunosuppressants that make them compatible with originally incompatible kidneys. We firstly present a general computational framework to model this problem. Our main contribution is a range of efficient algorithms that provide flexibility in terms of meeting meaningful objectives. Motivated by the current reality of kidney exchanges using sophisticated mathematical-programming-based clearing algorithms, we then present a general but scalable approach to optimal clearing with immunosuppression; we validate our approach on realistic data from a large fielded exchange.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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