Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
Clearing algorithms for barter exchange markets: enabling nationwide kidney exchanges
Proceedings of the 8th ACM conference on Electronic commerce
Online stochastic optimization in the large: application to kidney exchange
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
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
A random graph model of kidney exchanges: efficiency, individual-rationality and incentives
Proceedings of the 12th ACM conference on Electronic commerce
Optimizing kidney exchange with transplant chains: theory and reality
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
FOCS '12 Proceedings of the 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science
Kidney exchange in dynamic sparse heterogenous pools
Proceedings of the fourteenth ACM conference on Electronic commerce
Harnessing the power of two crossmatches
Proceedings of the fourteenth ACM conference on Electronic commerce
Harnessing the power of two crossmatches
Proceedings of the fourteenth ACM conference on Electronic commerce
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Most algorithmic matches in fielded kidney exchanges do not result in an actual transplant. In this paper, we address the problem of cycles and chains in a proposed match failing after the matching algorithm has committed to them. We show that failure-aware kidney exchange can significantly increase the expected number of lives saved (i) in theory, on random graph models; (ii) on real data from kidney exchange match runs between 2010 and 2012; (iii) on synthetic data generated via a model of dynamic kidney exchange. From the computational viewpoint, we design a branch-and-price-based optimal clearing algorithm specifically for the probabilistic exchange clearing problem and show that this new solver scales well on large simulated data, unlike prior clearing algorithms.