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  2. Maximal and minimal elements - Wikipedia

    en.wikipedia.org/wiki/Maximal_and_minimal_elements

    A minimal element of a subset of some preordered set is defined dually as an element of that is not greater than any other element in . The notions of maximal and minimal elements are weaker than those of greatest element and least element which are also known, respectively, as maximum and minimum.

  3. Binomial heap - Wikipedia

    en.wikipedia.org/wiki/Binomial_heap

    To delete the minimum element from the heap, first find this element, remove it from the root of its binomial tree, and obtain a list of its child subtrees (which are each themselves binomial trees, of distinct orders). Transform this list of subtrees into a separate binomial heap by reordering them from smallest to largest order.

  4. Range minimum query - Wikipedia

    en.wikipedia.org/wiki/Range_minimum_query

    Range minimum query reduced to the lowest common ancestor problem. Given an array A[1 … n] of n objects taken from a totally ordered set, such as integers, the range minimum query RMQ A (l,r) =arg min A[k] (with 1 ≤ l ≤ k ≤ r ≤ n) returns the position of the minimal element in the specified sub-array A[l … r].

  5. Priority queue - Wikipedia

    en.wikipedia.org/wiki/Priority_queue

    When only insert, find-min and extract-min are needed and in case of integer priorities, a bucket queue can be constructed as an array of C linked lists plus a pointer top, initially C. Inserting an item with key k appends the item to the k 'th list, and updates top ← min(top, k), both in constant time.

  6. Selection algorithm - Wikipedia

    en.wikipedia.org/wiki/Selection_algorithm

    As a baseline algorithm, selection of the th smallest value in a collection of values can be performed by the following two steps: . Sort the collection; If the output of the sorting algorithm is an array, retrieve its th element; otherwise, scan the sorted sequence to find the th element.

  7. Heap (data structure) - Wikipedia

    en.wikipedia.org/wiki/Heap_(data_structure)

    extract-max (or extract-min): returns the node of maximum value from a max heap [or minimum value from a min heap] after removing it from the heap (a.k.a., pop [5]) delete-max (or delete-min): removing the root node of a max heap (or min heap), respectively; replace: pop root and push a new key. This is more efficient than a pop followed by a ...

  8. Binary heap - Wikipedia

    en.wikipedia.org/wiki/Binary_heap

    The procedure for deleting the root from the heap (effectively extracting the maximum element in a max-heap or the minimum element in a min-heap) while retaining the heap property is as follows: Replace the root of the heap with the last element on the last level. Compare the new root with its children; if they are in the correct order, stop.

  9. Search data structure - Wikipedia

    en.wikipedia.org/wiki/Search_data_structure

    The simplest kind of query is to locate a record that has a specific field (the key) equal to a specified value v.Other common kinds of query are "find the item with smallest (or largest) key value", "find the item with largest key value not exceeding v", "find all items with key values between specified bounds v min and v max".