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  2. Parallel breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Parallel_breadth-first_search

    An example of CSR representation of a directed graph. Pennant data structure for k=0 to k=3. An example of bag structure with 23 elements. There are some special data structures that parallel BFS can benefit from, such as CSR (Compressed Sparse Row), bag-structure, bitmap and so on.

  3. Breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Breadth-first_search

    If G is a tree, replacing the queue of this breadth-first search algorithm with a stack will yield a depth-first search algorithm. For general graphs, replacing the stack of the iterative depth-first search implementation with a queue would also produce a breadth-first search algorithm, although a somewhat nonstandard one. [10]

  4. Best-first search - Wikipedia

    en.wikipedia.org/wiki/Best-first_search

    Best-first search is a class of search algorithms which explores a graph by expanding the most promising node chosen according to a specified rule.. Judea Pearl described best-first search as estimating the promise of node n by a "heuristic evaluation function () which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to ...

  5. Graph traversal - Wikipedia

    en.wikipedia.org/wiki/Graph_traversal

    A breadth-first search (BFS) is another technique for traversing a finite graph. BFS visits the sibling vertices before visiting the child vertices, and a queue is used in the search process. This algorithm is often used to find the shortest path from one vertex to another.

  6. Lexicographic breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Lexicographic_breadth...

    The algorithm is called lexicographic breadth-first search because the order it produces is an ordering that could also have been produced by a breadth-first search, and because if the ordering is used to index the rows and columns of an adjacency matrix of a graph then the algorithm sorts the rows and columns into lexicographical order.

  7. Sudoku solving algorithms - Wikipedia

    en.wikipedia.org/wiki/Sudoku_solving_algorithms

    Sudoku can be solved using stochastic (random-based) algorithms. [11] [12] An example of this method is to: Randomly assign numbers to the blank cells in the grid. Calculate the number of errors. "Shuffle" the inserted numbers until the number of mistakes is reduced to zero. A solution to the puzzle is then found.

  8. List of NP-complete problems - Wikipedia

    en.wikipedia.org/wiki/List_of_NP-complete_problems

    Domatic number [3]: GT3 Dominating set, a.k.a. domination number [3]: GT2 NP-complete special cases include the edge dominating set problem, i.e., the dominating set problem in line graphs. NP-complete variants include the connected dominating set problem and the maximum leaf spanning tree problem. [3]: ND2 Feedback vertex set [2] [3]: GT7

  9. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    By contrast, a breadth-first search will never reach the grandchildren, as it seeks to exhaust the children first. A more sophisticated analysis of running time can be given via infinite ordinal numbers ; for example, the breadth-first search of the depth 2 tree above will take ω ·2 steps: ω for the first level, and then another ω for the ...