The pairing heap: a new form of self-adjusting heap
Algorithmica
SIAM Journal on Computing
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
Purely functional data structures
Purely functional data structures
Worst-case efficient priority queues
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
On the efficiency of pairing heaps and related data structures
Journal of the ACM (JACM)
A data structure for manipulating priority queues
Communications of the ACM
Meldable heaps and boolean union-find
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Introduction to Algorithms
A programming and problem-solving seminar
A programming and problem-solving seminar
On the power of structural violations in priority queues
CATS '07 Proceedings of the thirteenth Australasian symposium on Theory of computing - Volume 65
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We introduce an adaptation of run-relaxed heaps which provides efficient heap operations with respect to the number of element comparisons performed. Our data structure guarantees the worst-case cost of O(1) for find–min, insert, and decrease; and the worst-case cost of O(lg n) with at most lg n + 3 lg lg n + O(1) element comparisons for delete, improving the bound of $3\lg n + O(1)$ on the number of element comparisons known for run-relaxed heaps. Here, n denotes the number of elements stored prior to the operation in question, and lg n equals max{1, log2n}.