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Algorithm Engineering [electronic resource] : Selected Results and Surveys / edited by Lasse Kliemann, Peter Sanders.

Contributor(s): Kliemann, Lasse [editor.] | Sanders, Peter [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Theoretical Computer Science and General Issues: 9220Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: X, 419 p. 68 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319494876.Subject(s): Algorithms | Application software | Artificial intelligence | Computer networks  | Computer science | Computer science -- Mathematics | Discrete mathematics | Algorithms | Computer and Information Systems Applications | Artificial Intelligence | Computer Communication Networks | Theory of Computation | Discrete Mathematics in Computer ScienceAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 518.1 Online resources: Click here to access online
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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