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  2. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    a depth-first search starting at the node A, assuming that the left edges in the shown graph are chosen before right edges, and assuming the search remembers previously visited nodes and will not repeat them (since this is a small graph), will visit the nodes in the following order: A, B, D, F, E, C, G.

  3. Strongly connected component - Wikipedia

    en.wikipedia.org/wiki/Strongly_connected_component

    The first, in the original graph, is used to choose the order in which the outer loop of the second depth-first search tests vertices for having been visited already and recursively explores them if not. The second depth-first search is on the transpose graph of the original graph, and each recursive exploration finds a single new strongly ...

  4. Iterative deepening depth-first search - Wikipedia

    en.wikipedia.org/wiki/Iterative_deepening_depth...

    a depth-first search starting at A, assuming that the left edges in the shown graph are chosen before right edges, and assuming the search remembers previously-visited nodes and will not repeat them (since this is a small graph), will visit the nodes in the following order: A, B, D, F, E, C, G.

  5. Reachability - Wikipedia

    en.wikipedia.org/wiki/Reachability

    This can be accomplished in linear time using algorithms such as breadth first search or iterative deepening depth-first search. [ 4 ] If you will be making many queries, then a more sophisticated method may be used; the exact choice of method depends on the nature of the graph being analysed.

  6. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    For example, given a binary tree of infinite depth, a depth-first search will go down one side (by convention the left side) of the tree, never visiting the rest, and indeed an in-order or post-order traversal will never visit any nodes, as it has not reached a leaf (and in fact never will). By contrast, a breadth-first (level-order) traversal ...

  7. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    A* is an informed search algorithm, or a best-first search, meaning that it is formulated in terms of weighted graphs: starting from a specific starting node of a graph, it aims to find a path to the given goal node having the smallest cost (least distance travelled, shortest time, etc.).

  8. Topological sorting - Wikipedia

    en.wikipedia.org/wiki/Topological_sorting

    An alternative algorithm for topological sorting is based on depth-first search.The algorithm loops through each node of the graph, in an arbitrary order, initiating a depth-first search that terminates when it hits any node that has already been visited since the beginning of the topological sort or the node has no outgoing edges (i.e., a leaf node):

  9. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    Breadth-first search: traverses a graph level by level; Brute-force search: an exhaustive and reliable search method, but computationally inefficient in many applications; D*: an incremental heuristic search algorithm; Depth-first search: traverses a graph branch by branch; Dijkstra's algorithm: a special case of A* for which no heuristic ...