Optimal Time-Space Tradeoff for the 2D Convex-Hull Problem

Darwish, Omar; Elmasry, Amr

doi:10.1007/978-3-662-44777-2_24

Cited by 24 publications

(21 citation statements)

References 14 publications

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“…For j ≥ I ≥ 1, predecessor and successor of ej are defined in RNGi regarding each endpoint w of ej as follows: the predecessor of ej is the half-edge in RNGi which has w as its head and is the first halfedge encountered in a counterclockwise sweep from ej around w [15]. The successor of ej is the half-edge in RNGi which has w as its tail and is the first halfedge encountered in a clockwise sweep from ej around w, as shown in Figure 2.…”

Section: Mathematical Formulationmentioning

confidence: 99%

Simultaneous Optimization of Electrical Interconnection Configuration in Onshore Wind Fields

Celeska

Krkoleva

Najdenkoski

et al. 2019

JEEIT

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The electrical interconnection cost of onshore wind fields (WF) is a part that should not be neglected in the design of WF. In order to minimize the investment and operational costs, this paper proposes an optimization formulation to find the optimal electrical interconnection configuration of wind turbines (WTs), simultaneously. This simultaneous minimization of total trenching length is done during а WF layout optimization by application of evolutional algorithm. In this paper, an algorithm is considered to comprehensively assess the optimal interconnection layout of the WTs. The interconnections are considerable fraction of the overall design cost of the WF. The optimal electrical interconnection design obtained by an algorithm with implemented Euclidean Minimum Spanning Tree method, corresponds to a lower cost and coupled with the technological developments can help policy makers and WF developers increase the use of onshore wind energy as a feasible unlimited renewable source of electrical energy.

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Section: Mathematical Formulationmentioning

confidence: 99%

Simultaneous Optimization of Electrical Interconnection Configuration in Onshore Wind Fields

Celeska

Krkoleva

Najdenkoski

et al. 2019

JEEIT

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“…In the algorithms literature, where the focus is also on improving time, a huge amount of research has been devoted to memory constrained algorithms, even as early as in the 1980s [38]. Early work on this focused on the selection problem [25,28,38,39], but more recently on computational geometry problems [3,6,9,21,26] and graph algorithms [24,4,8,34,17,32]. Regarding the data structure we develop to support findany operation, Elmasry et al [Lemma 2.1, [24]] state a data structure (without proof) that supports all the operations i.e., insert, search, delete and findany (they call it some id) among others, in constant time.…”

Section: Related Workmentioning

confidence: 99%

Space Efficient Linear Time Algorithms for BFS, DFS and Applications

et al. 2018

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Research on space efficient graph algorithms, particularly for st-connectivity, has a long history including the celebrated polynomial time, O(lg n) bits 3 algorithm in undirected graphs by Reingold (JACM 2008), and polynomial time, n/2 Θ( Some of these results were announced in preliminary form in the proceedings of 22nd International Computing and Combinatorics Conference (COCOON 2016), Springer LNCS volume 9797, pages 119-130 [7], and 27th International Symposium on Algorithms and Computation (ISAAC 2016), LIPIcs, volume 64, pages 22:1-22:13 [17]. More specifically, this paper contains the linear time algorithms for DFS and its applications, announced in [7] and [17], along with the linear time algorithms for BFS and a few other graph problems, announced in [7]. 3 We use lg to denote logarithm to the base 2.

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“…The optimal trade-offs for the sorting problem and the convex hull problem are known for both models (the random-access model and the multi-pass streaming model.) Under the random-access model, both problems can be solved in O(n 2 /(s log n) + n log(s log n)) time 3 using O(s) words of workspace [8,14]. Under the multi-pass streaming model, both problems can be solved in O(n 2 / log n+ n log s) time [7,13] using O(s) words of workspace and O(n/s) passes of the input array.…”

Section: Related Workmentioning

confidence: 99%

A Time-Space Trade-Off for Triangulations of Points in the Plane

Ahn

Baraldo

et al. 2017

Lecture Notes in Computer Science

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In this paper, we consider time-space trade-offs for reporting a triangulation of points in the plane. The goal is to minimize the amount of working space while keeping the total running time small. We present the first multi-pass algorithm on the problem that returns the edges of a triangulation with their adjacency information. This even improves the previously best known random-access algorithm.

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Optimal Time-Space Tradeoff for the 2D Convex-Hull Problem

Cited by 24 publications

References 14 publications

Simultaneous Optimization of Electrical Interconnection Configuration in Onshore Wind Fields

Simultaneous Optimization of Electrical Interconnection Configuration in Onshore Wind Fields

Space Efficient Linear Time Algorithms for BFS, DFS and Applications

A Time-Space Trade-Off for Triangulations of Points in the Plane

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