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  2. Havel–Hakimi algorithm - Wikipedia

    en.wikipedia.org/wiki/Havel–Hakimi_algorithm

    A simple graph contains no double edges or loops. [1] The degree sequence is a list of numbers in nonincreasing order indicating the number of edges incident to each vertex in the graph. [2] If a simple graph exists for exactly the given degree sequence, the list of integers is called graphic. The Havel-Hakimi algorithm constructs a special ...

  3. Parallel single-source shortest path algorithm - Wikipedia

    en.wikipedia.org/wiki/Parallel_single-source...

    A central problem in algorithmic graph theory is the shortest path problem. One of the generalizations of the shortest path problem is known as the single-source-shortest-paths (SSSP) problem, which consists of finding the shortest paths from a source vertex s {\displaystyle s} to all other vertices in the graph.

  4. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    Shortest path (A, C, E, D, F), blue, between vertices A and F in the weighted directed graph. In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized.

  5. Cut (graph theory) - Wikipedia

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

    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 belongs to the set T. In an unweighted undirected graph, the size or weight of a cut is the number of edges crossing the cut. In a weighted graph, the value or weight is defined by the sum of the weights of the edges crossing the ...

  6. Parallel breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Parallel_breadth-first_search

    The breadth-first-search algorithm is a way to explore the vertices of a graph layer by layer. It is a basic algorithm in graph theory which can be used as a part of other graph algorithms. For instance, BFS is used by Dinic's algorithm to find maximum flow in a graph.

  7. Assignment problem - Wikipedia

    en.wikipedia.org/wiki/Assignment_problem

    This is an unbalanced assignment problem. One way to solve it is to invent a fourth dummy task, perhaps called "sitting still doing nothing", with a cost of 0 for the taxi assigned to it. This reduces the problem to a balanced assignment problem, which can then be solved in the usual way and still give the best solution to the problem.

  8. Hamiltonian path problem - Wikipedia

    en.wikipedia.org/wiki/Hamiltonian_path_problem

    The problems of finding a Hamiltonian path and a Hamiltonian cycle can be related as follows: In one direction, the Hamiltonian path problem for graph G can be related to the Hamiltonian cycle problem in a graph H obtained from G by adding a new universal vertex x, connecting x to all vertices of G. Thus, finding a Hamiltonian path cannot be ...

  9. Longest path problem - Wikipedia

    en.wikipedia.org/wiki/Longest_path_problem

    In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.