Theory of Computing Systems

, Volume 39, Issue 1, pp 3–14 | Cite as

Matching Algorithms Are Fast in Sparse Random Graphs

  • Holger Bast
  • Kurt Mehlhorn
  • Guido Schafer
  • Hisao Tamaki


We present an improved average case analysis of the maximum cardinality matching problem. We show that in a bipartite or general random graph on n vertices, with high probability every non-maximum matching has an augmenting path of length O(log n). This implies that augmenting path algorithms like the Hopcroft-Karp algorithm for bipartite graphs and the Micali-Vazirani algorithm for general graphs, which have a worst case running time of O(m√n), run in time O(m log n) with high probability, where m is the number of edges in the graph. Motwani proved these results for random graphs when the average degree is at least ln (n) [Average Case Analysis of Algorithms for Matchings and Related Problems, Journal of the ACM, 41(6):1329-1356, 1994]. Our results hold if only the average degree is a large enough constant. At the same time we simplify the analysis of Motwani.


High Probability Computational Mathematic Bipartite Graph Relate Problem Random Graph 
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Copyright information

© Springer 2005

Authors and Affiliations

  1. 1.Max-Planck-Institut fur Informatik, Stuhlsatzenhausweg 85, 66123 SaarbruckenGermany
  2. 2.Meiji University, School of Science and Technology, 1-1-1 HigashiMita, Tama, Kawasaki 214-8571Japan

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