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The breadth-first-search algorithm is a way to explore the vertices of a graph layer by layer. It is a basic algorithm in graph theory which can be used as a part of other graph algorithms. For instance, BFS is used by Dinic's algorithm to find maximum flow in a graph.
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]
Since the number of BFS-s is finite and bounded by (), an optimal solution to any LP can be found in finite time by just evaluating the objective function in all () BFS-s. This is not the most efficient way to solve an LP; the simplex algorithm examines the BFS-s in a much more efficient way.
Long division is the standard algorithm used for pen-and-paper division of multi-digit numbers expressed in decimal notation. It shifts gradually from the left to the right end of the dividend, subtracting the largest possible multiple of the divisor (at the digit level) at each stage; the multiples then become the digits of the quotient, and the final difference is then the remainder.
Basic feasible solution, in linear programming; Be File System, the native file system for the Be Operating System; Best-first search, a path finding algorithm; Boot File System, a file system used on UnixWare to store files necessary to its boot process; Breadth-first search, a graph search algorithm
An early two-subproblem D&C algorithm that was specifically developed for computers and properly analyzed is the merge sort algorithm, invented by John von Neumann in 1945. [ 7 ] Another notable example is the algorithm invented by Anatolii A. Karatsuba in 1960 [ 8 ] that could multiply two n - digit numbers in O ( n log 2 3 ...
A naive algorithm could count the number of elements of each bucket. Then the elements could be inserted to the other array at the right place. Using this, one has to determine the bucket for each elements twice (one time for counting the number of elements in a bucket, and one time for inserting them).
The number of shortest paths between and every vertex is calculated using breadth-first search. The breadth-first search starts at s {\displaystyle s} , and the shortest distance d ( v ) {\displaystyle d(v)} of each vertex from s {\displaystyle s} is recorded, dividing the graph into discrete layers.