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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.
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.
There are classical sequential algorithms which solve this problem, such as Dijkstra's algorithm. In this article, however, we present two parallel algorithms solving this problem. Another variation of the problem is the all-pairs-shortest-paths (APSP) problem, which also has parallel approaches: Parallel all-pairs shortest path algorithm.
Like this algorithm, Tarjan's strongly connected components algorithm also uses depth first search together with a stack to keep track of vertices that have not yet been assigned to a component, and moves these vertices into a new component when it finishes expanding the final vertex of its component.
The Floyd–Warshall algorithm solves all pairs shortest paths. Johnson's algorithm solves all pairs' shortest paths, and may be faster than Floyd–Warshall on sparse graphs. Perturbation theory finds (at worst) the locally shortest path. Cherkassky et al. [10] provide more algorithms and associated evaluations.
Algorithms + Data Structures = Programs [1] is a 1976 book written by Niklaus Wirth covering some of the fundamental topics of system engineering, computer programming, particularly that algorithms and data structures are inherently related. For example, if one has a sorted list one will use a search algorithm optimal for sorted lists.
The Dijkstra–Scholten algorithm is a tree-based algorithm which can be described by the following: The initiator of a computation is the root of the tree. Upon receiving a computational message: If the receiving process is currently not in the computation: the process joins the tree by becoming a child of the sender of the message.
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 ...