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  2. Prune and search - Wikipedia

    en.wikipedia.org/wiki/Prune_and_search

    This resembles the recurrence for binary search but has a larger S(n) term than the constant term of binary search. In prune and search algorithms S(n) is typically at least linear (since the whole input must be processed). With this assumption, the recurrence has the solution T(n) = O(S(n)).

  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. Bitwise operation - Wikipedia

    en.wikipedia.org/wiki/Bitwise_operation

    A bitwise AND is a binary operation that takes two equal-length binary representations and performs the logical AND operation on each pair of the corresponding bits. Thus, if both bits in the compared position are 1, the bit in the resulting binary representation is 1 (1 × 1 = 1); otherwise, the result is 0 (1 × 0 = 0 and 0 × 0 = 0).

  5. Bitwise operations in C - Wikipedia

    en.wikipedia.org/wiki/Bitwise_operations_in_C

    It is just a representation of AND which does its work on the bits of the operands rather than the truth value of the operands. Bitwise binary AND performs logical conjunction (shown in the table above) of the bits in each position of a number in its binary form. For instance, working with a byte (the char type):

  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. Beam search - Wikipedia

    en.wikipedia.org/wiki/Beam_search

    The beam width bounds the memory required to perform the search. Since a goal state could potentially be pruned, beam search sacrifices completeness (the guarantee that an algorithm will terminate with a solution, if one exists). Beam search is not optimal (that is, there is no guarantee that it will find the best solution).

  8. Branch and bound - Wikipedia

    en.wikipedia.org/wiki/Branch_and_bound

    B will denote the best solution found so far, and will be used as an upper bound on candidate solutions. Initialize a queue to hold a partial solution with none of the variables of the problem assigned. Loop until the queue is empty: Take a node N off the queue. If N represents a single candidate solution x and f(x) < B, then x is the best ...

  9. Trie - Wikipedia

    en.wikipedia.org/wiki/Trie

    [24]: 3 The skip number 1 at node 0 corresponds to the position 1 in the binary encoded ASCII where the leftmost bit differed in the key set . [ 24 ] : 3-4 The skip number is crucial for search, insertion, and deletion of nodes in the Patricia tree, and a bit masking operation is performed during every iteration.