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  2. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    Dijkstra's algorithm (/ ˈ d aɪ k s t r ə z / DYKE-strəz) is an algorithm for finding the shortest paths between nodes in a weighted graph, which may represent, for example, a road network. It was conceived by computer scientist Edsger W. Dijkstra in 1956 and published three years later.

  3. Shortest-path tree - Wikipedia

    en.wikipedia.org/wiki/Shortest-path_tree

    In connected graphs where shortest paths are well-defined (i.e. where there are no negative-length cycles), we may construct a shortest-path tree using the following algorithm: Compute dist(u), the shortest-path distance from root v to vertex u in G using Dijkstra's algorithm or Bellman–Ford algorithm.

  4. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    From a dynamic programming point of view, Dijkstra's algorithm for the shortest path problem is a successive approximation scheme that solves the dynamic programming functional equation for the shortest path problem by the Reaching method. [8] [9] [10] In fact, Dijkstra's explanation of the logic behind the algorithm, [11] namely Problem 2.

  5. Pathfinding - Wikipedia

    en.wikipedia.org/wiki/Pathfinding

    A common example of a graph-based pathfinding algorithm is Dijkstra's algorithm. [3] This algorithm begins with a start node and an "open set" of candidate nodes. At each step, the node in the open set with the lowest distance from the start is examined.

  6. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    Use a shortest path algorithm (e.g., Dijkstra's algorithm, Bellman-Ford algorithm) to find the shortest path from the source node to the sink node in the residual graph. Augment the Flow: Find the minimum capacity along the shortest path. Increase the flow on the edges of the shortest path by this minimum capacity.

  7. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    Dijkstra's algorithm, as another example of a uniform-cost search algorithm, can be viewed as a special case of A* where ⁠ = ⁠ for all x. [ 12 ] [ 13 ] General depth-first search can be implemented using A* by considering that there is a global counter C initialized with a very large value.

  8. Path-based strong component algorithm - Wikipedia

    en.wikipedia.org/wiki/Path-based_strong...

    The algorithm performs a depth-first search of the given graph G, maintaining as it does two stacks S and P (in addition to the normal call stack for a recursive function). Stack S contains all the vertices that have not yet been assigned to a strongly connected component, in the order in which the depth-first search reaches the vertices.

  9. k shortest path routing - Wikipedia

    en.wikipedia.org/wiki/K_shortest_path_routing

    It can be solved using Yen's algorithm [3] [4] to find the lengths of all shortest paths from a fixed node to all other nodes in an n-node non negative-distance network, a technique requiring only 2n 2 additions and n 2 comparison, fewer than other available shortest path algorithms need.