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Abstract
In this paper, we propose a new approach, parallel iterative improvement (PII), to solving the stable matching problem. This approach treats the stable matching problem as an optimization problem with all possible matchings forming its solution space. Since a stable matching always exists for any stable matching problem instance, finding a stable matching is equivalent to finding a matching with the minimum number (which is always zero) of unstable pairs. A particular PII algorithm is presented to show the effectiveness of this approach by constructing a new matching from an existing matching and using techniques such as randomization and greedy selection to speedup the convergence process. Simulation results show that the PII algorithm has better average performance compared with the classical stable matching algorithms and converges inn iterations with high probability. The proposed algorithm is also useful for some real-time applications with stringent time constraint.
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Authors and Affiliations
Department of Computer Science, University of Texas at Dallas, Richardson, TX, 75083-0688, USA
Enyue Lu & S. Q. Zheng
- Enyue Lu
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- S. Q. Zheng
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Editors and Affiliations
University of Southern California, CA 90089-2562, Los Angeles
Timothy Mark Pinkston
Department of Electrical Engineering, University of Southern California, CA 90089-2562, Los Angeles, USA
Viktor K. Prasanna
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Lu, E., Zheng, S.Q. (2003). A Parallel Iterative Improvement Stable Matching Algorithm. In: Pinkston, T.M., Prasanna, V.K. (eds) High Performance Computing - HiPC 2003. HiPC 2003. Lecture Notes in Computer Science, vol 2913. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24596-4_7
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