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  2. Matching (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Matching_(graph_theory)

    The matching number of a graph G is the size of a maximum matching. Every maximum matching is maximal, but not every maximal matching is a maximum matching. The following figure shows examples of maximum matchings in the same three graphs. A perfect matching is a matching that matches all vertices of the graph. That is, a matching is perfect if ...

  3. Maximum cardinality matching - Wikipedia

    en.wikipedia.org/wiki/Maximum_cardinality_matching

    Maximum cardinality matching is a fundamental problem in graph theory. [1] We are given a graph G , and the goal is to find a matching containing as many edges as possible; that is, a maximum cardinality subset of the edges such that each vertex is adjacent to at most one edge of the subset.

  4. Kőnig's theorem (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Kőnig's_theorem_(graph...

    An example of a bipartite graph, with a maximum matching (blue) and minimum vertex cover (red) both of size six. In the mathematical area of graph theory, Kőnig's theorem, proved by Dénes Kőnig (), describes an equivalence between the maximum matching problem and the minimum vertex cover problem in bipartite graphs.

  5. Blossom algorithm - Wikipedia

    en.wikipedia.org/wiki/Blossom_algorithm

    The matching problem can be generalized by assigning weights to edges in G and asking for a set M that produces a matching of maximum (minimum) total weight: this is the maximum weight matching problem. This problem can be solved by a combinatorial algorithm that uses the unweighted Edmonds's algorithm as a subroutine. [6]

  6. Maximum weight matching - Wikipedia

    en.wikipedia.org/wiki/Maximum_weight_matching

    Maximum weight matching of 2 graphs. The first is also a perfect matching, while the second is far from it with 4 vertices unaccounted for, but has high value weights compared to the other edges in the graph. In computer science and graph theory, the maximum weight matching problem is the problem of finding, in a weighted graph, a matching in ...

  7. Matching in hypergraphs - Wikipedia

    en.wikipedia.org/wiki/Matching_in_hypergraphs

    The problem of finding a maximum-cardinality matching in a hypergraph, thus calculating (), is NP-hard even for 3-uniform hypergraphs (see 3-dimensional matching). This is in contrast to the case of simple (2-uniform) graphs in which computing a maximum-cardinality matching can be done in polynomial time.

  8. Tutte–Berge formula - Wikipedia

    en.wikipedia.org/wiki/Tutte–Berge_formula

    Therefore, by the Tutte–Berge formula, it has at most (1−3+16)/2 = 7 edges in any matching. In the mathematical discipline of graph theory the Tutte–Berge formula is a characterization of the size of a maximum matching in a graph.

  9. Perfect matching - Wikipedia

    en.wikipedia.org/wiki/Perfect_matching

    Every perfect matching is a maximum-cardinality matching, but the opposite is not true. For example, consider the following graphs: [1] In graph (b) there is a perfect matching (of size 3) since all 6 vertices are matched; in graphs (a) and (c) there is a maximum-cardinality matching (of size 2) which is not perfect, since some vertices are ...