enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Graph enumeration - Wikipedia

    en.wikipedia.org/wiki/Graph_enumeration

    The complete list of all free trees on 2, 3, and 4 labeled vertices: = tree with 2 vertices, = trees with 3 vertices, and = trees with 4 vertices.. In combinatorics, an area of mathematics, graph enumeration describes a class of combinatorial enumeration problems in which one must count undirected or directed graphs of certain types, typically as a function of the number of vertices of the ...

  3. Weisfeiler Leman graph isomorphism test - Wikipedia

    en.wikipedia.org/wiki/Weisfeiler_Leman_graph...

    In graph theory, the Weisfeiler Leman graph isomorphism test is a heuristic test for the existence of an isomorphism between two graphs G and H. [1] It is a generalization of the color refinement algorithm and has been first described by Weisfeiler and Leman in 1968. [ 2 ]

  4. Reachability - Wikipedia

    en.wikipedia.org/wiki/Reachability

    In graph theory, reachability refers to the ability to get from one vertex to another within a graph. A vertex s {\displaystyle s} can reach a vertex t {\displaystyle t} (and t {\displaystyle t} is reachable from s {\displaystyle s} ) if there exists a sequence of adjacent vertices (i.e. a walk ) which starts with s {\displaystyle s} and ends ...

  5. Hamiltonian path problem - Wikipedia

    en.wikipedia.org/wiki/Hamiltonian_path_problem

    To decide if a graph has a Hamiltonian path, one would have to check each possible path in the input graph G. There are n! different sequences of vertices that might be Hamiltonian paths in a given n-vertex graph (and are, in a complete graph), so a brute force search algorithm that tests all possible sequences would be very slow.

  6. Graph isomorphism problem - Wikipedia

    en.wikipedia.org/wiki/Graph_isomorphism_problem

    It is shown that finding an isomorphism for n-vertex graphs is equivalent to finding an n-clique in an M-graph of size n 2. This fact is interesting because the problem of finding a clique of order (1 − ε)n in a M-graph of size n 2 is NP-complete for arbitrarily small positive ε. [43] The problem of homeomorphism of 2-complexes. [44]

  7. Sudoku solving algorithms - Wikipedia

    en.wikipedia.org/wiki/Sudoku_solving_algorithms

    Unlike the latter however, optimisation algorithms do not necessarily require problems to be logic-solvable, giving them the potential to solve a wider range of problems. Algorithms designed for graph colouring are also known to perform well with Sudokus. [13] It is also possible to express a Sudoku as an integer linear programming problem ...

  8. Ramsey's theorem - Wikipedia

    en.wikipedia.org/wiki/Ramsey's_theorem

    Each complete graph K n has ⁠ 1 / 2 ⁠ n(n − 1) edges, so there would be a total of c n(n-1)/2 graphs to search through (for c colours) if brute force is used. [6] Therefore, the complexity for searching all possible graphs (via brute force ) is O ( c n 2 ) for c colourings and at most n nodes.

  9. Greedy coloring - Wikipedia

    en.wikipedia.org/wiki/Greedy_coloring

    The graphs that are both perfect graphs and -perfect graphs are exactly the chordal graphs. On even-hole-free graphs more generally, the degeneracy ordering approximates the optimal coloring to within at most twice the optimal number of colors; that is, its approximation ratio is 2. [20]