Algorithm engineering : selected results and surveys / Lasse Kliemann, Peter Sanders (eds.).
Material type:
TextSeries: Lecture notes in computer science ; 9220. | LNCS sublibrary. SL 1, Theoretical computer science and general issues.Publisher: Cham, Switzerland : Springer, 2016Description: 1 online resource (x, 419 pages) : illustrationsContent type: - text
- computer
- online resource
- 9783319494876
- 3319494872
- 3319494864
- 9783319494869
- Algorithms
- Computer algorithms
- Algorithmes
- algorithms
- Information retrieval
- Artificial intelligence
- Network hardware
- User interface design & usability
- Discrete mathematics
- Algorithms & data structures
- Computers -- Information Technology
- Computers -- Intelligence (AI) & Semantics
- Computers -- Hardware -- Network Hardware
- Computers -- Machine Theory
- Computers -- Data Processing
- Computers -- Programming -- Algorithms
- Computer algorithms
- Algorithms
- 518/.1 23
- QA9.58
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
eBook
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e-Library | eBook LNCS | Available |
Includes author index.
Online resource; title from PDF title page (SpringerLink, viewed November 22, 2016).
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.