Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Journal of Artificial Intelligence Research
When are elections with few candidates hard to manipulate?
Journal of the ACM (JACM)
Consensus Genetic Maps as Median Orders from Inconsistent Sources
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A Short Introduction to Computational Social Choice
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
Fixed-Parameter Algorithms for Kemeny Scores
AAIM '08 Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management
How similarity helps to efficiently compute Kemeny rankings
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Computing slater rankings using similarities among candidates
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Improved bounds for computing Kemeny rankings
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Nonexistence of voting rules that are usually hard to manipulate
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Fixed-parameter algorithms for Kemeny rankings
Theoretical Computer Science
Comparing multiagent systems research in combinatorial auctions and voting
Annals of Mathematics and Artificial Intelligence
Some representation and computational issues in social choice
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Kemeny elections with bounded single-peaked or single-crossing width
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We consider from a computational perspective the problem of how to aggregate the ranking preferences of a number of alternatives by a number of different voters into a single consensus ranking, following the majority voting rule. Social welfare functions for aggregating preferences in this way have been widely studied since the time of Condorcet (1785). One drawback of majority voting procedures when three or more alternatives are being ranked is the presence of cycles in the majority preference relation. The Kemeny order is a social welfare function whicll has been designed to tackle the presence of such cycles. However computing a Kemeny order is known to be NP-hard. We develop a greedy heuristic and an exact branch and bound procedure for computing Kemeny orders. We present results of a computational study on these procedures.