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  2. Longest path problem - Wikipedia

    en.wikipedia.org/wiki/Longest_path_problem

    Apply dynamic programming to this path decomposition to find a longest path in time (!), where is the number of vertices in the graph. Since the output path has length at least as large as d {\displaystyle d} , the running time is also bounded by O ( ℓ ! 2 ℓ n ) {\displaystyle O(\ell !2^{\ell }n)} , where ℓ {\displaystyle \ell } is the ...

  3. Pointer jumping - Wikipedia

    en.wikipedia.org/wiki/Pointer_jumping

    Pointer jumping or path doubling is a design technique for parallel algorithms that operate on pointer structures, such as linked lists and directed graphs. Pointer jumping allows an algorithm to follow paths with a time complexity that is logarithmic with respect to the length of the longest path.

  4. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    Edmonds' algorithm (also known as Chu–Liu/Edmonds' algorithm): find maximum or minimum branchings; Euclidean minimum spanning tree: algorithms for computing the minimum spanning tree of a set of points in the plane; Longest path problem: find a simple path of maximum length in a given graph; Minimum spanning tree. Borůvka's algorithm ...

  5. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    Dijkstra's algorithm finds the shortest path from a given source node to every other node. [7]: 196–206 It can be used to find the shortest path to a specific destination node, by terminating the algorithm after determining the shortest path to the destination node. For example, if the nodes of the graph represent cities, and the costs of ...

  6. Level ancestor problem - Wikipedia

    en.wikipedia.org/wiki/Level_ancestor_problem

    In fact in order to answer a level ancestor query, the algorithm needs to jump from a path to another until it reaches the root and there could be Θ(√ n) of such paths on a leaf-to-root path. This leads us to an algorithm that can pre-process the tree in O( n ) time and answers queries in O( √ n ).

  7. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    The algorithm described so far only gives the length of the shortest path. To find the actual sequence of steps, the algorithm can be easily revised so that each node on the path keeps track of its predecessor. After this algorithm is run, the ending node will point to its predecessor, and so on, until some node's predecessor is the start node.

  8. Widest path problem - Wikipedia

    en.wikipedia.org/wiki/Widest_path_problem

    In this graph, the widest path from Maldon to Feering has bandwidth 29, and passes through Clacton, Tiptree, Harwich, and Blaxhall. In graph algorithms, the widest path problem is the problem of finding a path between two designated vertices in a weighted graph, maximizing the weight of the minimum-weight edge in the path.

  9. Johnson's algorithm - Wikipedia

    en.wikipedia.org/wiki/Johnson's_algorithm

    The first three stages of Johnson's algorithm are depicted in the illustration below. The graph on the left of the illustration has two negative edges, but no negative cycles. The center graph shows the new vertex q, a shortest path tree as computed by the Bellman–Ford algorithm with q as starting vertex, and the values h(v) computed at each other node as the length of the shortest path from ...