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  2. Perfect matching - Wikipedia

    en.wikipedia.org/wiki/Perfect_matching

    In graph theory, a perfect matching in a graph is a matching that covers every vertex of the graph. More formally, given a graph G = (V, E), a perfect matching in G is a subset M of edge set E, such that every vertex in the vertex set V is adjacent to exactly one edge in M. A perfect matching is also called a 1-factor; see Graph factorization ...

  3. Matching (graph theory) - Wikipedia

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

    Matching (graph theory) In the mathematical discipline of graph theory, a matching or independent edge set in an undirected graph is a set of edges without common vertices. [1] In other words, a subset of the edges is a matching if each vertex appears in at most one edge of that matching. Finding a matching in a bipartite graph can be treated ...

  4. Stable marriage problem - Wikipedia

    en.wikipedia.org/wiki/Stable_marriage_problem

    Stable marriage problem. In mathematics, economics, and computer science, the stable marriage problem (also stable matching problem) is the problem of finding a stable matching between two equally sized sets of elements given an ordering of preferences for each element. A matching is a bijection from the elements of one set to the elements of ...

  5. List of NP-complete problems - Wikipedia

    en.wikipedia.org/wiki/List_of_NP-complete_problems

    Graph coloring [2] [3]: GT4 Graph homomorphism problem [3]: GT52 Graph partition into subgraphs of specific types (triangles, isomorphic subgraphs, Hamiltonian subgraphs, forests, perfect matchings) are known NP-complete. Partition into cliques is the same problem as coloring the complement of the given graph.

  6. Hall-type theorems for hypergraphs - Wikipedia

    en.wikipedia.org/wiki/Hall-type_theorems_for...

    In the mathematical field of graph theory, Hall-type theorems for hypergraphs are several generalizations of Hall's marriage theorem from graphs to hypergraphs. Such theorems were proved by Ofra Kessler, [ 1 ][ 2 ] Ron Aharoni, [ 3 ][ 4 ] Penny Haxell, [ 5 ][ 6 ] Roy Meshulam, [ 7 ] and others.

  7. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    Creating a matching Using a shortcut heuristic on the graph created by the matching above. The algorithm of Christofides and Serdyukov follows a similar outline but combines the minimum spanning tree with a solution of another problem, minimum-weight perfect matching. This gives a TSP tour which is at most 1.5 times the optimal.

  8. Assignment problem - Wikipedia

    en.wikipedia.org/wiki/Assignment_problem

    There is also a constant s which is at most the cardinality of a maximum matching in the graph. The goal is to find a minimum-cost matching of size exactly s. The most common case is the case in which the graph admits a one-sided-perfect matching (i.e., a matching of size r), and s=r. Unbalanced assignment can be reduced to a balanced assignment.

  9. Maximum cardinality matching - Wikipedia

    en.wikipedia.org/wiki/Maximum_cardinality_matching

    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.