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  2. Cut (graph theory) - Wikipedia

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

    A cut C = (S, T) is a partition of V of a graph G = (V, E) into two subsets S and T. The cut-set of a cut C = (S, T) is the set {(u, v) ∈ E | u ∈ S, v ∈ T} of edges that have one endpoint in S and the other endpoint in T. If s and t are specified vertices of the graph G, then an s – t cut is a cut in which s belongs to the set S and t ...

  3. Maximum common edge subgraph - Wikipedia

    en.wikipedia.org/wiki/Maximum_common_edge_subgraph

    The maximum common edge subgraph problem on general graphs is NP-complete as it is a generalization of subgraph isomorphism: a graph is isomorphic to a subgraph of another graph if and only if the maximum common edge subgraph of and has the same number of edges as .

  4. Graph theory - Wikipedia

    en.wikipedia.org/wiki/Graph_theory

    Often, the problem is to decompose a graph into subgraphs isomorphic to a fixed graph; for instance, decomposing a complete graph into Hamiltonian cycles. Other problems specify a family of graphs into which a given graph should be decomposed, for instance, a family of cycles, or decomposing a complete graph K n into n − 1 specified trees ...

  5. Vertex cover - Wikipedia

    en.wikipedia.org/wiki/Vertex_cover

    Example graph that has a vertex cover comprising 2 vertices (bottom), but none with fewer. In graph theory, a vertex cover (sometimes node cover) of a graph is a set of vertices that includes at least one endpoint of every edge of the graph. In computer science, the problem of finding a minimum vertex cover is a classical optimization problem.

  6. Maximum cut - Wikipedia

    en.wikipedia.org/wiki/Maximum_cut

    In a graph, a maximum cut is a cut whose size is at least the size of any other cut. That is, it is a partition of the graph's vertices into two complementary sets S and T, such that the number of edges between S and T is as large as possible. Finding such a cut is known as the max-cut problem. The problem can be stated simply as follows.

  7. Boundary (graph theory) - Wikipedia

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

    The edge boundary is the set of edges with one endpoint in the inner boundary and one endpoint in the outer boundary. [ 1 ] These boundaries and their sizes are particularly relevant for isoperimetric problems in graphs , separator theorems , minimum cuts , expander graphs , and percolation theory .

  8. Matching (graph theory) - Wikipedia

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

    A vertex is matched (or saturated) if it is an endpoint of one of the edges in the matching. Otherwise the vertex is unmatched (or unsaturated). A maximal matching is a matching M of a graph G that is not a subset of any other matching. A matching M of a graph G is maximal if every edge in G has a non-empty intersection with at least one edge ...

  9. Crossing number (graph theory) - Wikipedia

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

    A drawing of the Heawood graph with three crossings. This is the minimum number of crossings among all drawings of this graph, so the graph has crossing number cr(G) = 3.. In graph theory, the crossing number cr(G) of a graph G is the lowest number of edge crossings of a plane drawing of the graph G.