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  2. Level ancestor problem - Wikipedia

    en.wikipedia.org/wiki/Level_ancestor_problem

    Consider a path P consisting of n nodes rooted at a node r. We can store the path into an array of size n called Ladder and we can quickly answer a level ancestor query of LA(v, d) by returning Ladder[d] if depth(v)≤d. This will take O(1). However, this will only work if the given tree is a path. Otherwise, we need to decompose it into paths.

  3. k shortest path routing - Wikipedia

    en.wikipedia.org/wiki/K_shortest_path_routing

    insert path p s = {s} into B with cost 0 while B is not empty and count t < K: – let p u be the shortest cost path in B with cost C – B = B − {p u}, count u = count u + 1 – if u = t then P = P U {p u} – if count u ≤ K then for each vertex v adjacent to u: – let p v be a new path with cost C + w(u, v) formed by concatenating edge ...

  4. Local consistency - Wikipedia

    en.wikipedia.org/wiki/Local_consistency

    Path consistency is a property similar to arc consistency, but considers pairs of variables instead of only one. A pair of variables is path-consistent with a third variable if each consistent evaluation of the pair can be extended to the other variable in such a way that all binary constraints are satisfied.

  5. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    After every stage, dynamic programming makes decisions based on all the decisions made in the previous stage and may reconsider the previous stage's algorithmic path to the solution. Optimal substructure "A problem exhibits optimal substructure if an optimal solution to the problem contains optimal solutions to the sub-problems." [2]

  6. Longest path problem - Wikipedia

    en.wikipedia.org/wiki/Longest_path_problem

    In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.

  7. AVL tree - Wikipedia

    en.wikipedia.org/wiki/AVL_tree

    It is the first self-balancing binary search tree data structure to be invented. [ 3 ] AVL trees are often compared with red–black trees because both support the same set of operations and take O ( log ⁡ n ) {\displaystyle {\text{O}}(\log n)} time for the basic operations.

  8. Stern–Brocot tree - Wikipedia

    en.wikipedia.org/wiki/Stern–Brocot_tree

    The path from the root 1 to a number q in the Stern–Brocot tree may be found by a binary search algorithm, which may be expressed in a simple way using mediants. Augment the non-negative rational numbers to including a value ⁠ 1 / 0 ⁠ (representing +∞) that is by definition greater than all other rationals.

  9. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    Solution of a travelling salesman problem: the black line shows the shortest possible loop that connects every red dot. In the theory of computational complexity, the travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the ...