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  2. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    Find the Shortest Path: 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.

  3. SMA* - Wikipedia

    en.wikipedia.org/wiki/SMA*

    SMA* or Simplified Memory Bounded A* is a shortest path algorithm based on the A* algorithm. The main advantage of SMA* is that it uses a bounded memory, while the A* algorithm might need exponential memory. All other characteristics of SMA* are inherited from A*.

  4. Category:Graph algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Graph_algorithms

    Parallel all-pairs shortest path algorithm; Parallel breadth-first search; Parallel single-source shortest path algorithm; Path-based strong component algorithm; Pre-topological order; Prim's algorithm; Proof-number search; Push–relabel maximum flow algorithm

  5. Bidirectional search - Wikipedia

    en.wikipedia.org/wiki/Bidirectional_search

    Bidirectional search is a graph search algorithm that finds a shortest path from an initial vertex to a goal vertex in a directed graph. It runs two simultaneous searches: one forward from the initial state, and one backward from the goal, stopping when the two meet.

  6. Euclidean shortest path - Wikipedia

    en.wikipedia.org/wiki/Euclidean_shortest_path

    There are many results on computing shortest paths which stays on a polyhedral surface. Given two points s and t, say on the surface of a convex polyhedron, the problem is to compute a shortest path that never leaves the surface and connects s with t. This is a generalization of the problem from 2-dimension but it is much easier than the 3 ...

  7. 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 to all other vertices in the graph.

  8. 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 ...

  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 ...

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