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  2. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    One example is the constrained shortest path problem, [16] which attempts to minimize the total cost of the path while at the same time maintaining another metric below a given threshold. This makes the problem NP-complete (such problems are not believed to be efficiently solvable for large sets of data, see P = NP problem ).

  3. 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 ...

  4. Floyd–Warshall algorithm - Wikipedia

    en.wikipedia.org/wiki/Floyd–Warshall_algorithm

    The Floyd–Warshall algorithm is an example of dynamic programming, and was published in its currently recognized form by Robert Floyd in 1962. [3] However, it is essentially the same as algorithms previously published by Bernard Roy in 1959 [4] and also by Stephen Warshall in 1962 [5] for finding the transitive closure of a graph, [6] and is closely related to Kleene's algorithm (published ...

  5. Contraction hierarchies - Wikipedia

    en.wikipedia.org/wiki/Contraction_hierarchies

    The shortest path in a graph can be computed using Dijkstra's algorithm but, given that road networks consist of tens of millions of vertices, this is impractical. [1] Contraction hierarchies is a speed-up method optimized to exploit properties of graphs representing road networks. [2] The speed-up is achieved by creating shortcuts in a ...

  6. Optimal substructure - Wikipedia

    en.wikipedia.org/wiki/Optimal_substructure

    Consider finding a shortest path for traveling between two cities by car, as illustrated in Figure 1. Such an example is likely to exhibit optimal substructure. That is, if the shortest route from Seattle to Los Angeles passes through Portland and then Sacramento, then the shortest route from Portland to Los Angeles must pass through Sacramento too.

  7. Edge disjoint shortest pair algorithm - Wikipedia

    en.wikipedia.org/wiki/Edge_Disjoint_Shortest...

    Edge disjoint shortest pair algorithm is an algorithm in computer network routing. [1] The algorithm is used for generating the shortest pair of edge disjoint paths between a given pair of vertices. For an undirected graph G(V, E), it is stated as follows: Run the shortest path algorithm for the given pair of vertices

  8. 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 ...

  9. Parallel all-pairs shortest path algorithm - Wikipedia

    en.wikipedia.org/wiki/Parallel_all-pairs...

    A central problem in algorithmic graph theory is the shortest path problem. Hereby, the problem of finding the shortest path between every pair of nodes is known as all-pair-shortest-paths (APSP) problem. As sequential algorithms for this problem often yield long runtimes, parallelization has shown to be beneficial in this field. In this ...