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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 ...
To turn a regular search tree into an order statistic tree, the nodes of the tree need to store one additional value, which is the size of the subtree rooted at that node (i.e., the number of nodes below it). All operations that modify the tree must adjust this information to preserve the invariant that size[x] = size[left[x]] + size[right[x]] + 1
The priority search tree is used to store a set of 2-dimensional points ordered by priority and by a key value. This is accomplished by creating a hybrid of a priority queue and a binary search tree. The result is a tree where each node represents a point in the original dataset. The point contained by the node is the one with the lowest priority.
In a simple case, the intervals do not overlap and they can be inserted into a simple binary search tree and queried in () time. However, with arbitrarily overlapping intervals, there is no way to compare two intervals for insertion into the tree since orderings sorted by the beginning points or the ending points may be different.
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 ...
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
In this way, deletion is reduced to the problem of removing a node with 0 or 1 children. Unlike a binary search tree, in a splay tree after deletion, we splay the parent of the removed node to the top of the tree. Alternatively: The node to be deleted is first splayed, i.e. brought to the root of the tree and then deleted.
Newton's method in optimization (can be used to search for where the derivative is zero) Golden-section search (similar to ternary search, useful if evaluating f takes most of the time per iteration) Binary search algorithm (can be used to search for where the derivative changes in sign) Interpolation search; Exponential search; Linear search