enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Reverse-delete algorithm - Wikipedia

    en.wikipedia.org/wiki/Reverse-delete_algorithm

    Since deleting the edge will not further disconnect the graph, the edge is then deleted. The next largest edge is edge BD so the algorithm will check this edge and delete the edge. The next edge to check is edge EG, which will not be deleted since it would disconnect node G from the graph. Therefore, the next edge to delete is edge BC.

  3. Prim's algorithm - Wikipedia

    en.wikipedia.org/wiki/Prim's_algorithm

    These algorithms find the minimum spanning forest in a possibly disconnected graph; in contrast, the most basic form of Prim's algorithm only finds minimum spanning trees in connected graphs. However, running Prim's algorithm separately for each connected component of the graph, it can also be used to find the minimum spanning forest. [9]

  4. Dinic's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dinic's_algorithm

    Dinic's algorithm or Dinitz's algorithm is a strongly polynomial algorithm for computing the maximum flow in a flow network, conceived in 1970 by Israeli (formerly Soviet) computer scientist Yefim Dinitz. [1]

  5. Search algorithm - Wikipedia

    en.wikipedia.org/wiki/Search_algorithm

    Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...

  6. Kruskal's algorithm - Wikipedia

    en.wikipedia.org/wiki/Kruskal's_algorithm

    Kruskal's algorithm [1] finds a minimum spanning forest of an undirected edge-weighted graph.If the graph is connected, it finds a minimum spanning tree.It is a greedy algorithm that in each step adds to the forest the lowest-weight edge that will not form a cycle. [2]

  7. Iterative deepening depth-first search - Wikipedia

    en.wikipedia.org/wiki/Iterative_deepening_depth...

    The edges traversed in this search form a Trémaux tree, a structure with important applications in graph theory. Performing the same search without remembering previously visited nodes results in visiting nodes in the order A, B, D, F, E, A, B, D, F, E, etc. forever, caught in the A, B, D, F, E cycle and never reaching C or G.

  8. Push–relabel maximum flow algorithm - Wikipedia

    en.wikipedia.org/wiki/Push–relabel_maximum_flow...

    Since 𝓁(s) = | V |, 𝓁(t) = 0, and there are no paths longer than | V | − 1 in G f, in order for 𝓁(s) to satisfy the valid labeling condition s must be disconnected from t. At initialisation, the algorithm fulfills this requirement by creating a pre-flow f that saturates all out-arcs of s , after which 𝓁( v ) = 0 is trivially valid ...

  9. Connected-component labeling - Wikipedia

    en.wikipedia.org/wiki/Connected-component_labeling

    The method of defining the linked list specifies the use of a depth or a breadth first search. For this particular application, there is no difference which strategy to use. The simplest kind of a last in first out queue implemented as a singly linked list will result in a depth first search strategy.