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Algorithm Engineering [electronic resource] : Selected Results and Surveys /

Contributor(s): Material type: TextTextSeries: Theoretical Computer Science and General Issues ; 9220Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016Description: X, 419 p. 68 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319494876
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 518.1 23
LOC classification:
  • QA76.9.A43
Online resources:
Contents:
Engineering a Lightweight and Efficient Local Search SAT Solver -- Route Planning in Transportation Networks -- Theoretical Analysis of the k-Means Algorithm - A Survey -- Recent Advances in Graph Partitioning -- How to Generate Randomized Roundings with Dependencies and How to Derandomize Them -- External-Memory State Space Search -- Algorithm Engineering Aspects of Real-Time Rendering Algorithms -- Algorithm Engineering in Robust Optimization -- Clustering Evolving Networks -- Integrating Sequencing and Scheduling: A Generic Approach with Two Exemplary Industrial Applications -- Engineering a Bipartite Matching Algorithm in the Semi-Streaming Model -- Engineering Art Galleries.
In: Springer Nature eBookSummary: Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice.
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Engineering a Lightweight and Efficient Local Search SAT Solver -- Route Planning in Transportation Networks -- Theoretical Analysis of the k-Means Algorithm - A Survey -- Recent Advances in Graph Partitioning -- How to Generate Randomized Roundings with Dependencies and How to Derandomize Them -- External-Memory State Space Search -- Algorithm Engineering Aspects of Real-Time Rendering Algorithms -- Algorithm Engineering in Robust Optimization -- Clustering Evolving Networks -- Integrating Sequencing and Scheduling: A Generic Approach with Two Exemplary Industrial Applications -- Engineering a Bipartite Matching Algorithm in the Semi-Streaming Model -- Engineering Art Galleries.

Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice.

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