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Tarjan's strongly connected components algorithm is an algorithm in graph theory for finding the strongly connected components (SCCs) of a directed graph. It runs in linear time , matching the time bound for alternative methods including Kosaraju's algorithm and the path-based strong component algorithm .
In graph theory, Edmonds' algorithm or Chu–Liu/Edmonds' algorithm is an algorithm for finding a spanning arborescence of minimum weight (sometimes called an optimum branching) [1]. It is the directed analog of the minimum spanning tree problem.
FKT algorithm; Flood fill; Graph exploration algorithm; Matching (graph theory) Max flow min cut theorem; Maximum-cardinality search; Shortest path. Dijkstra's algorithm; Bellman–Ford algorithm; A* algorithm; Floyd–Warshall algorithm; Topological sorting. Pre-topological order
The unification of two argument graphs is defined as the most general graph (or the computation thereof) that is consistent with (i.e. contains all of the information in) the inputs, if such a graph exists; efficient unification algorithms are known.
Graph algorithms solve problems related to graph theory. Subcategories. This category has the following 3 subcategories, out of 3 total. ...
The Misra & Gries edge coloring algorithm is a polynomial time algorithm in graph theory that finds an edge coloring of any simple graph. The coloring produced uses at most Δ + 1 {\displaystyle \Delta +1} colors, where Δ {\displaystyle \Delta } is the maximum degree of the graph.
The basic form of the Bron–Kerbosch algorithm is a recursive backtracking algorithm that searches for all maximal cliques in a given graph G.More generally, given three disjoint sets of vertices R, P, and X, it finds the maximal cliques that include all of the vertices in R, some of the vertices in P, and none of the vertices in X.
There are a great number of algorithms that exploit this property and are therefore able to compute the shortest path a lot quicker than would be possible on general graphs. All of these algorithms work in two phases. In the first phase, the graph is preprocessed without knowing the source or target node. The second phase is the query phase.