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  2. Binary heap - Wikipedia

    en.wikipedia.org/wiki/Binary_heap

    The decrease key operation replaces the value of a node with a given value with a lower value, and the increase key operation does the same but with a higher value. This involves finding the node with the given value, changing the value, and then down-heapifying or up-heapifying to restore the heap property. Decrease key can be done as follows:

  3. Strict Fibonacci heap - Wikipedia

    en.wikipedia.org/wiki/Strict_Fibonacci_heap

    The decrease-key operation requires a reference to the node we wish to decrease the key of. However, the decrease-key operation itself sometimes swaps the key of a node and the key root. Assume that the insert operation returns some opaque reference that we can call decrease-key on, as part of the public API.

  4. Fibonacci heap - Wikipedia

    en.wikipedia.org/wiki/Fibonacci_heap

    This flexibility allows some operations to be executed in a lazy manner, postponing the work for later operations. For example, merging heaps is done simply by concatenating the two lists of trees, and operation decrease key sometimes cuts a node from its parent and forms a new tree.

  5. Heap (data structure) - Wikipedia

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

    However, there is no standard support for the replace, sift-up/sift-down, or decrease/increase-key operations. The Boost C++ libraries include a heaps library. Unlike the STL, it supports decrease and increase operations, and supports additional types of heap: specifically, it supports d-ary, binomial, Fibonacci, pairing and skew heaps.

  6. Pairing heap - Wikipedia

    en.wikipedia.org/wiki/Pairing_heap

    A pairing heap is either an empty heap, or a pairing tree consisting of a root element and a possibly empty list of pairing trees. The heap ordering property requires that parent of any node is no greater than the node itself. The following description assumes a purely functional heap that does not support the decrease-key operation.

  7. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    A min-priority queue is an abstract data type that provides 3 basic operations: add_with_priority(), decrease_priority() and extract_min(). As mentioned earlier, using such a data structure can lead to faster computing times than using a basic queue. Notably, Fibonacci heap [19] or Brodal queue offer optimal implementations for those 3 ...

  8. Binomial heap - Wikipedia

    en.wikipedia.org/wiki/Binomial_heap

    A binomial heap is implemented as a set of binomial trees that satisfy the binomial heap properties: [1] Each binomial tree in a heap obeys the minimum-heap property: the key of a node is greater than or equal to the key of its parent. There can be at most one binomial tree for each order, including zero order.

  9. 2–3 heap - Wikipedia

    en.wikipedia.org/wiki/2–3_heap

    The actual cost will be the number of comparisons performed during the operation. Note that the potential of an empty heap is 0. Decrease Key The number of nodes on trunks can increase or decrease during the removal of a tree, depending on the size of the workspace. The change in potential and number of comparisons can be observed in each case ...