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A Parallel Iterative Improvement Stable Matching Algorithm

  • Enyue Lu
  • S. Q. Zheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2913)

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 in n iterations with high probability. The proposed algorithm is also useful for some real-time applications with stringent time constraint.

Keywords

Parallel Algorithm Initiation Phase Stable Match Ranking List Ranking Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Enyue Lu
    • 1
  • S. Q. Zheng
    • 1
  1. 1.Department of Computer ScienceUniversity of Texas at DallasRichardsonUSA

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