Abstract
We propose a new greedy algorithm for the maximum cardinality matching problem. We give experimental evidence that this algorithm is likely to find a maximum matching in random graphs with constant expected degree c > 0, independent of the value of c. This is contrary to the behavior of commonly used greedy matching heuristics which are known to have some range of c where they probably fail to compute a maximum matching.
Keywords
- Bipartite Graph
- Greedy Algorithm
- Random Graph
- Reduction Step
- General Graph
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.
Research supported by DFG grant DI 412/10-2.
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Dietzfelbinger, M., Peilke, H., Rink, M. (2012). A More Reliable Greedy Heuristic for Maximum Matchings in Sparse Random Graphs. In: Klasing, R. (eds) Experimental Algorithms. SEA 2012. Lecture Notes in Computer Science, vol 7276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30850-5_14
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DOI: https://doi.org/10.1007/978-3-642-30850-5_14
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