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A More Reliable Greedy Heuristic for Maximum Matchings in Sparse Random Graphs

机译:稀疏随机图中最大匹配的更可靠的贪婪启发式算法

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摘要

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.
机译:针对最大基数匹配问题,我们提出了一种新的贪婪算法。我们提供了实验证据,表明该算法很可能在恒定期望度c> 0的随机图中找到最大匹配,而与c的值无关。这与常用的贪婪匹配启发式算法的行为相反,已知的贪婪匹配启发式算法具有大约c的范围,在这些范围内它们可能无法计算最大匹配。

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