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Violation heaps: A better substitute for Fibonacci heaps
, 812
"... We give a priority queue that achieves the same amortized bounds as Fibonacci heaps. Namely, findmin requires O(1) worstcase time, insert, meld and decreasekey require O(1) amortized time, and deletemin requires O(log n) amortized time. Our structure is simple and promises a more efficient pract ..."
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We give a priority queue that achieves the same amortized bounds as Fibonacci heaps. Namely, findmin requires O(1) worstcase time, insert, meld and decreasekey require O(1) amortized time, and deletemin requires O(log n) amortized time. Our structure is simple and promises a more efficient practical behavior compared to any other known Fibonaccilike heap. 1
RankPairing Heaps
"... Abstract. We introduce the rankpairing heap, a heap (priority queue) implementation that combines the asymptotic efficiency of Fibonacci heaps with much of the simplicity of pairing heaps. Unlike all other heap implementations that match the bounds of Fibonacci heaps, our structure needs only one c ..."
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Abstract. We introduce the rankpairing heap, a heap (priority queue) implementation that combines the asymptotic efficiency of Fibonacci heaps with much of the simplicity of pairing heaps. Unlike all other heap implementations that match the bounds of Fibonacci heaps, our structure needs only one cut and no other structural changes per key decrease; the trees representing the heap can evolve to have arbitrary structure. Our initial experiments indicate that rankpairing heaps perform almost as well as pairing heaps on typical input sequences and better on worstcase sequences. 1
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 ..."
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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 ..."
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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