The pairing heap: a new form of self-adjusting heap
Algorithmica
Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
Relaxed heaps: an alternative to Fibonacci heaps with applications to parallel computation
Communications of the ACM
Pairing heaps: experiments and analysis
Communications of the ACM
Weight-biased leftist trees and modified skip lists
Journal of Experimental Algorithmics (JEA)
On the efficiency of pairing heaps and related data structures
Journal of the ACM (JACM)
LEDA: a platform for combinatorial and geometric computing
LEDA: a platform for combinatorial and geometric computing
A data structure for manipulating priority queues
Communications of the ACM
Discrete Applied Mathematics - Special issue: Special issue devoted to the fifth annual international computing and combinatories conference (COCOON'99) Tokyo, Japan 26-28 July 1999
On the Performance of WEAK-HEAPSORT
STACS '00 Proceedings of the 17th Annual Symposium on Theoretical Aspects of Computer Science
Linear lists and priority queues as balanced binary trees
Linear lists and priority queues as balanced binary trees
Implementing HEAPSORT with (n logn - 0.9n) and QUICKSORT with (n logn + 0.2n) comparisons
Journal of Experimental Algorithmics (JEA)
ACM Transactions on Algorithms (TALG)
Acta Informatica
ACM Transactions on Algorithms (TALG)
Policy-based benchmarking of weak heaps and their relatives,
SEA'10 Proceedings of the 9th international conference on Experimental Algorithms
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In typical applications, a priority queue is used to execute a sequence of n insert, m decrease, and n delete-min operations, starting with an empty structure. We study the performance of different priority queues for this type of operation sequences both theoretically and experimentally. In particular, we focus on weak heaps, weak queues, and their relaxed variants. We prove that for relaxed weak heaps the execution of any such sequence requires at most 2m + 1.5n lg n element comparisons. This improves over the best bound, at most 2m + 2.89n lg n element comparisons, known for the existing variants of Fibonacci heaps. We programmed six members of the weak-heap family of priority queues. For random data sets, experimental results show that non-relaxed versions are performing best and that rank-relaxed versions are slightly faster than run-relaxed versions. Compared to weak-heap variants, the corresponding weak-queue variants are slightly better in time but not in the number of element comparisons.