Introduction to Algorithms
Eisenberg-Gale markets: algorithms and structural properties
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Bidding languages for combinatorial auctions
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Algorithms for strategyproof classification
Artificial Intelligence
Mechanism design on discrete lines and cycles
Proceedings of the 13th ACM Conference on Electronic Commerce
Beyond dominant resource fairness: extensions, limitations, and indivisibilities
Proceedings of the 13th ACM Conference on Electronic Commerce
Mechanism design for fair division: allocating divisible items without payments
Proceedings of the fourteenth ACM conference on Electronic commerce
Matching "versus" mechanism design
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In the course allocation problem, a university administrator seeks to efficiently and fairly allocate schedules of over-demanded courses to students with heterogeneous preferences. We investigate how to computationally implement a recently-proposed theoretical solution to this problem (Budish, 2009) which uses approximate competitive equilibria to balance notions of efficiency, fairness, and incentives. Despite the apparent similarity to the well-known combinatorial auction problem we show that no polynomial-size mixed-integer program (MIP) can solve our problem. Instead, we develop a two-level search process: at the master level, the center uses tabu search over the union of two distinct neighborhoods to suggest prices; at the agent level, we use MIPs to solve for student demands in parallel at the current prices. Our method scales near-optimally in the number of processors used and is able to solve realistic-size problems fast enough to be usable in practice.