TL;DR: The structure, Fibonacci heaps (abbreviated F-heaps), extends the binomial queues proposed by Vuillemin and studied further by Brown to obtain improved running times for several network optimization algorithms.
Abstract: In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, Fibonacci heaps (abbreviated F-heaps), extends the binomial queues proposed by Vuillemin and studied further by Brown. F-heaps support arbitrary deletion from an n-item heap in 0(log n) amortized time and all other standard heap operations in 0(1) amortized time. Using F-heaps we are able to obtain improved running times for several network optimization algorithms.
TL;DR: A data structure is described which can be used for representing a collection of priority queues and the primitive operations are insertion, deletion, union, update, and search for an item of earliest priority.
Abstract: A data structure is described which can be used for representing a collection of priority queues. The primitive operations are insertion, deletion, union, update, and search for an item of earliest priority.
TL;DR: A new form of heap is described, intended to be competitive with the Fibonacci heap in theory and easy to implement and fast in practice, and a partial complexity analysis of pairing heaps is provided.
Abstract: Recently, Fredman and Tarjan invented a new, especially efficient form of heap (priority queue) called theFibonacci heap. Although theoretically efficient, Fibonacci heaps are complicated to implement and not as fast in practice as other kinds of heaps. In this paper we describe a new form of heap, called thepairing heap, intended to be competitive with the Fibonacci heap in theory and easy to implement and fast in practice. We provide a partial complexity analysis of pairing heaps. Complete analysis remains an open problem.
TL;DR: The relaxed heap is a priority queue data structure that achieves the same amortized time bounds as the Fibonacci heap—a sequence of m decrease_key and n delete_min operations takes time O(m + n log n).
Abstract: The relaxed heap is a priority queue data structure that achieves the same amortized time bounds as the Fibonacci heap—a sequence of m decrease_key and n delete_min operations takes time O(m + n log n). A variant of relaxed heaps achieves similar bounds in the worst case—O(1) time for decrease_key and O(log n) for delete_min. Relaxed heaps give a processor-efficient parallel implementation of Dijkstra's shortest path algorithm, and hence other algorithms in network optimization. A relaxed heap is a type of binomial queue that allows heap order to be violated.