Handbook of combinatorics (vol. 1)
Handbook of combinatorics (vol. 1)
An efficient cost scaling algorithm for the assignment problem
Mathematical Programming: Series A and B
LEDA: a platform for combinatorial and geometric computing
LEDA: a platform for combinatorial and geometric computing
A Decomposition Theorem for Maximum Weight Bipartite Matchings
SIAM Journal on Computing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
ACM Transactions on Algorithms (TALG)
Popular matchings in the capacitated house allocation problem
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Reducing rank-maximal to maximum weight matching
Theoretical Computer Science
Sampling stable marriages: why spouse-swapping won't work
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
SIAM Journal on Computing
Heuristic initialization for bipartite matching problems
Journal of Experimental Algorithmics (JEA)
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
Theoretical Computer Science
Bounded Unpopularity Matchings
Algorithmica
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part I
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We experimentally study the problem of assigning applicants to posts. Each applicant provides a preference list, which may contain ties, ranking a subset of the posts. Different optimization criteria may be defined, which depend on the desired solution properties. The main focus of this work is to assess the quality of matchings computed by rank-maximal and popular matching algorithms and compare this with the minimum weight matching algorithm, which is a standard matching algorithm that is used in practice. Both rank-maximal and popular matching algorithms use common algorithmic techniques, which makes them excellent candidates for a running time comparison. Since popular matchings do not always exist, we also study the unpopularity of matchings computed by the aforementioned algorithms. Finally, extra criteria like total weight and cardinality are included, due to their importance in practice. All experiments are performed using structured random instances as well as instances created using real-world datasets.