Results 1 
5 of
5
Pairing heaps with O(log log n) decrease cost
 In 20th ACMSIAM Symposium on Discrete Algorithms
, 2009
"... We give a variation of the pairing heaps for which the time bounds for all the operations match the lower bound proved by Fredman for a family of similar selfadjusting heaps. Namely, our heap structure requires O(1) for insert and findmin, O(log n) for deletemin, and O(log log n) for decreasekey a ..."
Abstract

Cited by 5 (2 self)
 Add to MetaCart
We give a variation of the pairing heaps for which the time bounds for all the operations match the lower bound proved by Fredman for a family of similar selfadjusting heaps. Namely, our heap structure requires O(1) for insert and findmin, O(log n) for deletemin, and O(log log n) for decreasekey and meld (all the bounds are in the amortized sense except for findmin). 1
Thin Heaps, Thick Heaps
, 2006
"... The Fibonacci heap was devised to provide an especially efficient implementation of Dijkstra’s shortest path algorithm. Although asyptotically efficient, it is not as fast in practice as other heap implementations. Expanding on ideas of Høyer, we describe three heap implementations (two versions of ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
The Fibonacci heap was devised to provide an especially efficient implementation of Dijkstra’s shortest path algorithm. Although asyptotically efficient, it is not as fast in practice as other heap implementations. Expanding on ideas of Høyer, we describe three heap implementations (two versions of thin heaps and one of thick heaps) that have the same amortized efficiency as Fibonacci heaps but need less space and promise better practical performance. As part of our development, we fill in a gap in Høyer’s analysis.
Strict Fibonacci Heaps
"... Wepresentthefirstpointerbasedheapimplementationwith time bounds matching those of Fibonacci heaps in the worst case. We support makeheap, insert, findmin, meld and decreasekey in worstcase O(1) time, and delete and deletemin in worstcase O(lgn) time, where n is the size of the heap. The data s ..."
Abstract
 Add to MetaCart
Wepresentthefirstpointerbasedheapimplementationwith time bounds matching those of Fibonacci heaps in the worst case. We support makeheap, insert, findmin, meld and decreasekey in worstcase O(1) time, and delete and deletemin in worstcase O(lgn) time, where n is the size of the heap. The data structure uses linear space. A previous, very complicated, solution achieving the same time bounds in the RAM model made essential use of arrays and extensive use of redundant counter schemes to maintain balance. Our solution uses neither. Our key simplification is to discard the structure of the smaller heap when doing a meld. We use the pigeonhole principle in place of the redundant counter mechanism.
Pairing Heaps with Costless Meld
, 903
"... Improving the structure and analysis in [1], we give a variation of the pairing heaps that has amortized zero cost per meld (compared to an O(log log n) in [1]) and the same amortized bounds for all other operations. More precisely, the new pairing heap requires: no cost per meld, O(1) per findmin ..."
Abstract
 Add to MetaCart
Improving the structure and analysis in [1], we give a variation of the pairing heaps that has amortized zero cost per meld (compared to an O(log log n) in [1]) and the same amortized bounds for all other operations. More precisely, the new pairing heap requires: no cost per meld, O(1) per findmin and insert, O(log n) per deletemin, and O(log log n) per decreasekey. These bounds are the best known for any selfadjusting heap, and match the lower bound proven by Fredman for a family of such heaps. Moreover, our structure is even simpler than that in [1]. 1