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Priority queue: A priority queue is an abstract concept like "a list" or "a map"; just as a list can be implemented with a linked list or an array, a priority queue can be implemented with a heap or a variety of other methods. K-way merge: A heap data structure is useful to merge many already-sorted input streams into a single sorted output ...
The semantics of priority queues naturally suggest a sorting method: insert all the elements to be sorted into a priority queue, and sequentially remove them; they will come out in sorted order. This is actually the procedure used by several sorting algorithms , once the layer of abstraction provided by the priority queue is removed.
This makes the min-max heap a very useful data structure to implement a double-ended priority queue. Like binary min-heaps and max-heaps, min-max heaps support logarithmic insertion and deletion and can be built in linear time. [3] Min-max heaps are often represented implicitly in an array; [4] hence it's referred to as an implicit data structure.
This can be done by additionally extracting the associated priority p from the queue and only processing further if p == dist[u] inside the while Q is not empty loop. [20] These alternatives can use entirely array-based priority queues without decrease-key functionality, which have been found to achieve even faster computing times in practice.
The designers chose to address this problem with a four-step solution: 1) Introducing a compiler switch that indicates if Java 1.4 or later should be used, 2) Only marking assert as a keyword when compiling as Java 1.4 and later, 3) Defaulting to 1.3 to avoid rendering prior (non 1.4 aware code) invalid and 4) Issue warnings, if the keyword is ...
The bucket queue is the priority-queue analogue of pigeonhole sort (also called bucket sort), a sorting algorithm that places elements into buckets indexed by their priorities and then concatenates the buckets. Using a bucket queue as the priority queue in a selection sort gives a form of the pigeonhole sort algorithm. [2]
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create-queue(q): create an empty kinetic priority queue q; find-max(q, t) (or find-min): - return the max (or min for a min-queue) value stored in the queue q at the current virtual time t. insert(X, f X, t): - insert a key X into the kinetic queue at the current virtual time t, whose value changes as a continuous function f X (t) of time t.