scholarly journals Preface

2019 ◽  
Vol 28 (4) ◽  
pp. 483-484
Author(s):  
Hsien-Kuei Hwang ◽  
Ralph Neininger ◽  
Marek Zaionc
Keyword(s):  
Data Structures ◽  
Analysis Of Algorithms ◽  
Probabilistic Methods ◽  
Algorithms And Data Structures ◽  
Special Issue ◽  
Rich Variety ◽  
Cost Distribution ◽  
Discrete Structures ◽  
Measure Of Performance ◽  
The Cost

This special issue is devoted to the Mathematical Analysis of Algorithms, which aims to predict the performance of fundamental algorithms and data structures in general use in Computer Science. The simplest measure of performance is the expected value of a cost function under natural models of randomness for the data, and finer properties of the cost distribution provide a deeper understanding of the complexity. Research in this area, which is intimately connected to combinatorics and random discrete structures, uses a rich variety of combinatorial, analytic and probabilistic methods.

scholarly journals Special Issue on “Algorithm Engineering: Towards Practically Efficient Solutions to Combinatorial Problems”

Algorithms ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 229
Author(s):  
Mattia D’Emidio ◽  
Daniele Frigioni
Keyword(s):  
Data Structures ◽  
Efficient Solutions ◽  
Combinatorial Problems ◽  
Algorithm Engineering ◽  
Original Research ◽  
Algorithms And Data Structures ◽  
Special Issue ◽  
Methodological Issues ◽  
Memory Hierarchies ◽  
Discrete Algorithms

The purpose of this special issue of Algorithms was to attract papers presenting original research in the area of algorithm engineering. In particular, submissions concerning the design, analysis, implementation, tuning, and experimental evaluation of discrete algorithms and data structures, and/or addressing methodological issues and standards in algorithmic experimentation were encouraged. Papers dealing with advanced models of computing, including memory hierarchies, cloud architectures, and parallel processing were also welcome. In this regard, we solicited contributions from all most prominent areas of applied algorithmic research, which include but are not limited to graphs, databases, computational geometry, big data, networking, combinatorial aspects of scientific computing, and computational problems in the natural sciences or engineering.

scholarly journals Special Issue on Algorithms and Data Structures (WADS 2019)

Algorithmica ◽  
2021 ◽  
Vol 83 (3) ◽  
pp. 775-775
Author(s):  
Zachary Friggstad ◽  
Jörg-Rüdiger Sack ◽  
Mohammad R. Salavatipour
Keyword(s):  
Data Structures ◽  
Algorithms And Data Structures ◽  
Special Issue

Computer algorithms

2018 ◽  
Author(s):  
Mark Newman
Keyword(s):  
Data Structures ◽  
Analysis Of Algorithms ◽  
Shortest Paths ◽  
Minimum Cut ◽  
Network Data ◽  
Computer Algorithms ◽  
Breadth First Search ◽  
Augmenting Path ◽  
Basic Concepts ◽  
Maximum Flows

This chapter introduces some of the fundamental concepts of numerical network calculations. The chapter starts with a discussion of basic concepts of computational complexity and data structures for storing network data, then progresses to the description and analysis of algorithms for a range of network calculations: breadth-first search and its use for calculating shortest paths, shortest distances, components, closeness, and betweenness; Dijkstra's algorithm for shortest paths and distances on weighted networks; and the augmenting path algorithm for calculating maximum flows, minimum cut sets, and independent paths in networks.

Sign in / Sign up

Export Citation Format

Share Document