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  2. Clique problem - Wikipedia

    en.wikipedia.org/wiki/Clique_problem

    The maximum clique problem may be solved using as a subroutine an algorithm for the maximal clique listing problem, because the maximum clique must be included among all the maximal cliques. [ 17 ] In the k -clique problem, the input is an undirected graph and a number k .

  3. Clique (graph theory) - Wikipedia

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

    A maximum clique transversal of a graph is a subset of vertices with the property that each maximum clique of the graph contains at least one vertex in the subset. [2] The opposite of a clique is an independent set, in the sense that every clique corresponds to an independent set in the complement graph.

  4. List of NP-complete problems - Wikipedia

    en.wikipedia.org/wiki/List_of_NP-complete_problems

    Examples include biological or social networks, which contain hundreds, thousands and even billions of nodes in some cases (e.g. Facebook or LinkedIn). 1-planarity [1] 3-dimensional matching [2] [3]: SP1 Bandwidth problem [3]: GT40 Bipartite dimension [3]: GT18 Capacitated minimum spanning tree [3]: ND5

  5. Clique cover - Wikipedia

    en.wikipedia.org/wiki/Clique_cover

    The clique cover problem in computational complexity theory is the algorithmic problem of finding a minimum clique cover, or (rephrased as a decision problem) finding a clique cover whose number of cliques is below a given threshold. Finding a minimum clique cover is NP-hard, and its decision version is NP-complete.

  6. Bron–Kerbosch algorithm - Wikipedia

    en.wikipedia.org/wiki/Bron–Kerbosch_algorithm

    In computer science, the Bron–Kerbosch algorithm is an enumeration algorithm for finding all maximal cliques in an undirected graph.That is, it lists all subsets of vertices with the two properties that each pair of vertices in one of the listed subsets is connected by an edge, and no listed subset can have any additional vertices added to it while preserving its complete connectivity.

  7. Tree decomposition - Wikipedia

    en.wikipedia.org/wiki/Tree_decomposition

    The tree decomposition of a graph is far from unique; for example, a trivial tree decomposition contains all vertices of the graph in its single root node. A tree decomposition in which the underlying tree is a path graph is called a path decomposition, and the width parameter derived from these special types of tree decompositions is known as ...

  8. Clique graph - Wikipedia

    en.wikipedia.org/wiki/Clique_graph

    A clique of a graph G is a set X of vertices of G with the property that every pair of distinct vertices in X are adjacent in G. A maximal clique of a graph G is a clique X of vertices of G, such that there is no clique Y of vertices of G that contains all of X and at least one other vertex. Given a graph G, its clique graph K(G) is a graph ...

  9. MaxCliqueDyn algorithm - Wikipedia

    en.wikipedia.org/wiki/MaxCliqueDyn_algorithm

    This algorithm was designed by Janez Konc and its description was published in 2007. [1] In comparison to earlier algorithms, MaxCliqueDyn has an improved coloring algorithm (ColorSort) and applies tighter, more computationally expensive upper bounds on a fraction of the search space. [1] Both improvements reduce time to find maximum clique.