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ABSTRACT
The pairing heap has recently been introduced as a new data structure for priority queues. Pairing heaps are extremely simple to implement and seem to be very efficient in practice, but they are difficult to analyze theoretically, and open problems remain. It has been conjectured that they achieve the same amortized time bounds as Fibonacci heaps, namely, O(log n) time for delete and delete_min and O(1) for all other operations, where n is the size of the priority queue at the time of the operation. We provide empirical evidence that supports this conjecture. The most promising algorithm in our simulations is a new variant of the twopass method, called auxiliary twopass. We prove that, assuming no decrease_key operations are performed, it achieves the same amortized time bounds as Fibonacci heaps.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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1
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2
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Brown. M.R. Implementation and analysis of binomial queue algorithms. SIAM J. Comput. 7 (Aug. 1978), 298-319.
|
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3
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Crane, C.A. Linear lists and priority queues as balanced binary trees. Tech. Rep. STAN-CS-72259, Dept. of Computer Science, Stanford University, Feb. 1972.
|
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4
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Fredman, M.L., and Tarjan. R.E. Fibonacci heaps and their uses in improved network optimization algorithms. In Proceedings of the 25th Annual Symposium on Foundations of Computer Science, (West Palm Beach, Fla.. Oct. 1984), 338-344.
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5
|
|
 |
6
|
|
| |
7
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|
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8
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Tarjan. R.E. Amortized computational complexity. SIAM J Algorithm Disc. Mefh. 6 (Apr. 1985). 306-316.
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9
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|
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10
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Williams, J.W.J. Algorithm 232: Heapsort. Commun. ACM 7, 6 (June 1964),347-348.
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