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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:
In computer science, a heap is a tree-based data structure that satisfies the heap property: In a max heap, for any given node C, if P is the parent node of C, then the key (the value) of P is greater than or equal to the key of C. In a min heap, the key of P is less than or equal to the key of C. [1] The node at the "top" of the heap (with no ...
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.
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 ...
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.
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.
In computer science, the Brodal queue is a heap/priority queue structure with very low worst case time bounds: () for insertion, find-minimum, meld (merge two queues) and decrease-key and (()) for delete-minimum and general deletion. They are the first heap variant to achieve these bounds without resorting to amortization of operational costs.
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 ...