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  2. Matching (graph theory) - Wikipedia

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

    A maximum matching (also known as maximum-cardinality matching [2]) is a matching that contains the largest possible number of edges. There may be many maximum matchings. 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.

  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. Maximum weight matching - Wikipedia

    en.wikipedia.org/wiki/Maximum_weight_matching

    In computer science and graph theory, the maximum weight matching problem is the problem of finding, in a weighted graph, a matching in which the sum of weights is maximized. A special case of it is the assignment problem , in which the input is restricted to be a bipartite graph , and the matching constrained to be have cardinality that of the ...

  5. Hopcroft–Karp algorithm - Wikipedia

    en.wikipedia.org/wiki/Hopcroft–Karp_algorithm

    Maximum cardinality matching, the problem solved by the algorithm, and its generalization to non-bipartite graphs; Assignment problem, a generalization of this problem on weighted graphs, solved e.g. by the Hungarian algorithm; Edmonds–Karp algorithm for finding maximum flow, a generalization of the Hopcroft–Karp algorithm

  6. 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]

  7. Maximally matchable edge - Wikipedia

    en.wikipedia.org/wiki/Maximally_matchable_edge

    A matching in G is a subset M of E, such that each vertex in V is adjacent to at most a single edge in M. A maximum matching is a matching of maximum cardinality. An edge e in E is called maximally matchable (or allowed) if there exists a maximum matching M that contains e.

  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. Berge's theorem - Wikipedia

    en.wikipedia.org/wiki/Berge's_theorem

    Let M be a maximum matching and consider an alternating chain such that the edges in the path alternates between being and not being in M.If the alternating chain is a cycle or a path of even length starting on an unmatched vertex, then a new maximum matching M ′ can be found by interchanging the edges found in M and not in M.