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  2. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    From a dynamic programming point of view, Dijkstra's algorithm is a successive approximation scheme that solves the dynamic programming functional equation for the shortest path problem by the Reaching method. [33] [34] [35] In fact, Dijkstra's explanation of the logic behind the algorithm: [36] Problem 2.

  3. 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.

  4. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    So, they find the probability distribution of total travel duration using different optimization methods such as dynamic programming and Dijkstra's algorithm. [28] These methods use stochastic optimization, specifically stochastic dynamic programming to find the shortest path in networks with probabilistic arc length. [29]

  5. Pathfinding - Wikipedia

    en.wikipedia.org/wiki/Pathfinding

    Algorithms such as A* and Dijkstra's algorithm strategically eliminate paths, either through heuristics or through dynamic programming. By eliminating impossible paths, these algorithms can achieve time complexities as low as O ( | E | log ⁡ ( | V | ) ) {\displaystyle O(|E|\log(|V|))} .

  6. Parallel all-pairs shortest path algorithm - Wikipedia

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

    The Dijkstra algorithm originally was proposed as a solver for the single-source-shortest-paths problem. However, the algorithm can easily be used for solving the All-Pair-Shortest-Paths problem by executing the Single-Source variant with each node in the role of the root node. In pseudocode such an implementation could look as follows:

  7. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    One of the earliest applications of dynamic programming is the Held–Karp algorithm, which solves the problem in time (). [24] This bound has also been reached by Exclusion-Inclusion in an attempt preceding the dynamic programming approach. Solution to a symmetric TSP with 7 cities using brute force search.

  8. Dining philosophers problem - Wikipedia

    en.wikipedia.org/wiki/Dining_philosophers_problem

    In computer science, the dining philosophers problem is an example problem often used in concurrent algorithm design to illustrate synchronization issues and techniques for resolving them. It was originally formulated in 1965 by Edsger Dijkstra as a student exam exercise, presented in terms of computers competing for access to tape drive ...

  9. Dijkstra–Scholten algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra–Scholten_algorithm

    The Dijkstra–Scholten algorithm (named after Edsger W. Dijkstra and Carel S. Scholten) is an algorithm for detecting termination in a distributed system. [1] [2] The algorithm was proposed by Dijkstra and Scholten in 1980. [3] First, consider the case of a simple process graph which is a tree. A distributed computation which is tree ...