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Binary search Visualization of the binary search algorithm where 7 is the target value Class Search algorithm Data structure Array Worst-case performance O (log n) Best-case performance O (1) Average performance O (log n) Worst-case space complexity O (1) Optimal Yes In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search ...
Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...
In computer science, a dichotomic search is a search algorithm that operates by selecting between two distinct alternatives (dichotomies [1] or polychotomies [2] when they are more than two) at each step. It is a specific type of divide and conquer algorithm. A well-known example is binary search. [3]
Uniform binary search is an optimization of the classic binary search algorithm invented by Donald Knuth and given in Knuth's The Art of Computer Programming.It uses a lookup table to update a single array index, rather than taking the midpoint of an upper and a lower bound on each iteration; therefore, it is optimized for architectures (such as Knuth's MIX) on which
A Binary Search Tree is a node-based data structure where each node contains a key and two subtrees, the left and right. For all nodes, the left subtree's key must be less than the node's key, and the right subtree's key must be greater than the node's key. These subtrees must all qualify as binary search trees.
The static optimality problem is the optimization problem of finding the binary search tree that minimizes the expected search time, given the + probabilities. As the number of possible trees on a set of n elements is ( 2 n n ) 1 n + 1 {\displaystyle {2n \choose n}{\frac {1}{n+1}}} , [ 2 ] which is exponential in n , brute-force search is not ...
Given an array A of n elements with values A 0... A n−1, and target value T, the following subroutine uses a multiplicative binary search to find the index of T in A. Set i to 0; if i ≥ n, the search terminates unsuccessfully. if A i = T, the search is done; return i. if A i < T, set i to 2×i + 1 and go to step 2. if A i > T, set i to 2×i ...
Step 2. [Compare] If K < K i, go to Step 3; if K > K i go to Step 4; and if K = K i, the algorithm terminates successfully. Step 3. [Decrease i] If q=0, the algorithm terminates unsuccessfully. Otherwise set (i, p, q) ← (i − q, q, p − q) (which moves p and q one position back in the Fibonacci sequence); then return to Step 2. Step 4.