Computer Science Building, Rooms 150 & 151
Faculty Host: Victor Lesser
In kidney exchanges, patients with kidney disease can obtain compatible donors by swapping their own willing but incompatible donors. The clearing problem involves finding a social welfare maximizing set of non-overlapping short cycles. We proved this NP-hard. It was one of the main obstacles to a national kidney exchange. We presented the first algorithm capable of clearing these exchanges optimally on a nationwide scale. The key was incremental problem formulation because the formulation that gives tight LP bounds is too large to even store. On top of the branch-and-price paradigm we developed techniques that dramatically improve runtime and memory usage. Furthermore, clearing is actually an online problem where patient-donor pairs and altruistic donors appear and expire over time. We developed trajectory-based online stochastic optimization algorithms (that use our optimal offline solver as a subroutine) for this. I will discuss design parameters and tradeoffs. Our best online algorithms outperform the current practice of solving each batch separately. I will share experiences from using our algorithms as the clearing engine of the largest two kidney exchange networks in the US. We also introduced several design enhancements to the exchanges. For one, we used our algorithms to launch the first never-ending altruistic donor chains. I am also helping UNOS design the nationwide kidney exchange, which will use our algorithms; I will discuss current design considerations.
The talk covers material from the following papers:
Tuomas Sandholm is Professor in the Computer Science Department at Carnegie Mellon University. He has published over 380 papers on electronic commerce; game theory; artificial intelligence; multiagent systems; auctions and exchanges; automated negotiation and contracting; coalition formation; voting; safe exchange; normative models of bounded rationality; resource-bounded reasoning; machine learning; networks; and combinatorial optimization. He has 19 years of experience building optimization-based electronic marketplaces, and has fielded several of his systems. He is also Founder, Chairman, and Chief Scientist of CombineNet, Inc., which has commercialized over 800 large-scale generalized combinatorial auctions, with over $50 billion in total spend and over $6 billion in generated savings. He received the Ph.D. and M.S. degrees in computer science from the University of Massachusetts at Amherst in 1996 and 1994. He earned an M.S. (B.S. included) with distinction in Industrial Engineering and Management Science from the Helsinki University of Technology, Finland, in 1991. He is recipient of the National Science Foundation Career Award, the inaugural ACM Autonomous Agents Research Award, the Alfred P. Sloan Foundation Fellowship, and the Computers and Thought Award. He is Fellow of the ACM and AAAI.
A reception will be held at 3:40 PM in the atrium, outside the presentation room.