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Related papers: The Violation Heap: A Relaxed Fibonacci-Like Heap

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A lower bound is presented which shows that a class of heap algorithms in the pointer model with only heap pointers must spend Omega(log log n / log log log n) amortized time on the decrease-key operation (given O(log n) amortized-time…

Data Structures and Algorithms · Computer Science 2013-07-17 John Iacono

We introduce a new family of priority-queue data structures: partition-based simple heaps. The structures consist of $O(\log n)$ doubly-linked lists; order is enforced among data in different lists, but the individual lists are unordered.…

Data Structures and Algorithms · Computer Science 2026-03-03 Gerth Stølting Brodal , John Iacono , Casper Moldrup Rysgaard , Sebastian Wild

The Fibonacci heap is a classic data structure that supports deletions in logarithmic amortized time and all other heap operations in O(1) amortized time. We explore the design space of this data structure. We propose a version with the…

Data Structures and Algorithms · Computer Science 2014-07-23 Haim Kaplan , Robert E. Tarjan , Uri Zwick

We are concentrating on reducing overhead of heaps based on comparisons with optimal worstcase behaviour. The paper is inspired by Strict Fibonacci Heaps [1], where G. S. Brodal, G. Lagogiannis, and R. E. Tarjan implemented the heap with…

Data Structures and Algorithms · Computer Science 2019-11-27 Vladan Majerech

The pairing heap is a simple "self-adjusting" implementation of a heap (priority queue). Inserting an item into a pairing heap or decreasing the key of an item takes O(1) time worst-case, as does melding two heaps. But deleting an item of…

Data Structures and Algorithms · Computer Science 2022-08-26 Corwin Sinnamon , Robert Tarjan

A Fibonacci heap is a deterministic data structure implementing a priority queue with optimal amortized operation costs. An unfortunate aspect of Fibonacci heaps is that they must maintain a "mark bit" which serves only to ensure efficiency…

Data Structures and Algorithms · Computer Science 2015-02-19 Jerry Li , John Peebles

We analyze priority queues of Fibonacci family. The paper is inspired by Violation heap [1], where A. Elmasry saves one pointer in representation of Fibonacci heap nodes while achieving the same amortized bounds as Fibonacci heaps [2] of M.…

Data Structures and Algorithms · Computer Science 2019-03-01 Vladan Majerech

The heap is a basic data structure used in a wide variety of applications, including shortest path and minimum spanning tree algorithms. In this paper we explore the design space of comparison-based, amortized-efficient heap…

Data Structures and Algorithms · Computer Science 2009-03-03 Bernhard Haeupler , Siddhartha Sen , Robert E. Tarjan

We introduce the hollow heap, a very simple data structure with the same amortized efficiency as the classical Fibonacci heap. All heap operations except delete and delete-min take $O(1)$ time, worst case as well as amortized; delete and…

Data Structures and Algorithms · Computer Science 2015-10-23 Thomas Dueholm Hansen , Haim Kaplan , Robert E. Tarjan , Uri Zwick

We improve the lower bound on the amortized cost of the decrease-key operation in the pure heap model and show that any pure-heap-model heap (that has a \bigoh{\log n} amortized-time extract-min operation) must spend \bigom{\log\log n}…

Data Structures and Algorithms · Computer Science 2014-07-25 John Iacono , Özgür Özkan

We show the $O(\log n)$ time extract minimum function of efficient priority queues can be generalized to the extraction of the $k$ smallest elements in $O(k \log(n/k))$ time (we define $\log(x)$ as $\max(\log_2(x), 1)$.), which we prove…

Data Structures and Algorithms · Computer Science 2022-01-11 Bryce Sandlund , Lingyi Zhang

The smooth heap and the closely related slim heap are recently invented self-adjusting implementations of the heap (priority queue) data structure. We analyze the efficiency of these data structures. We obtain the following amortized bounds…

Data Structures and Algorithms · Computer Science 2021-11-08 Corwin Sinnamon , Robert E. Tarjan

Let $n$ denote the number of elements currently in a data structure. An in-place heap is stored in the first $n$ locations of an array, uses $O(1)$ extra space, and supports the operations: minimum, insert, and extract-min. We introduce an…

Data Structures and Algorithms · Computer Science 2014-07-15 Stefan Edelkamp , Jyrki Katajainen , Amr Elmasry

In the paper "Fast Fibonacci heaps with worst case extensions", we have described heaps with both Meld-DecreaseKey and DecreaseKey interfaces, allowing operations with guaranteed worst-case asymptotically optimal times. The paper was…

Data Structures and Algorithms · Computer Science 2020-11-20 Vladan Majerech

Link-based data structures, such as linked lists and binary search trees, have many well-known rearrangement steps allowing for efficient implementations of insertion, deletion, and other operations. We describe a rearrangement primitive…

Data Structures and Algorithms · Computer Science 2012-03-02 Boris Alexeev , M. Brian Jacokes

Since the invention of the pairing heap by Fredman, Sedgewick, Sleator, and Tarjan, it has been an open question whether this or any other simple "self-adjusting" heap supports decrease-key operations in $O(\log\log n)$ time, where $n$ is…

Data Structures and Algorithms · Computer Science 2025-02-13 Corwin Sinnamon , Robert E. Tarjan

Chazelle [JACM00] introduced the soft heap as a building block for efficient minimum spanning tree algorithms, and recently Kaplan et al. [SOSA2019] showed how soft heaps can be applied to achieve simpler algorithms for various selection…

Data Structures and Algorithms · Computer Science 2020-08-13 Gerth Stølting Brodal

We investigate the limits of one of the fundamental ideas in data structures: fractional cascading. This is an important data structure technique to speed up repeated searches for the same key in multiple lists and it has numerous…

Data Structures and Algorithms · Computer Science 2020-11-05 Peyman Afshani

The binary heap of Williams (1964) is a simple priority queue characterized by only storing an array containing the elements and the number of elements $n$ - here denoted a strictly implicit priority queue. We introduce two new strictly…

Data Structures and Algorithms · Computer Science 2015-05-04 Gerth Stølting Brodal , Jesper Sindahl Nielsen , Jakob Truelsen

We consider the classic problem of designing heaps. Standard binary heaps run faster in practice than Fibonacci heaps but have worse time guarantees. Here we present a new type of heap, a layered heap, that runs faster in practice than both…

Data Structures and Algorithms · Computer Science 2015-10-13 Peter Huggins
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