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Overview: Evolutionary Algorithms
- Evolutionary algorithm (EA) is an umbrella term used to describe population-based stochastic direct search algorithms that in some sense mimic natural evolution. Prominent representatives of such algorithms are genetic algorithms, evolution strategies, evolutionary programming, and genetic programming. On the basis of the evolutionary cycle, similarities and differences between these algorithms are described. We briefly discuss how EAs can be adapted to work well in case of multiple objectives, and dynamic or noisy optimization problems. We look at the tuning of algorithms and present some recent developments coming from theory. Finally, typical applications of EAs to real-world problems are shown, with special emphasis on data-mining applications
Author: | Thomas Bartz-BeielsteinGND, Jürgen Branke, Jörn Mehnen, Olaf Mersmann |
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URN: | urn:nbn:de:hbz:832-cos-777 |
Series (Serial Number): | CIplus (2/2015) |
Document Type: | Report |
Language: | German |
Year of Completion: | 2015 |
Release Date: | 2015/02/20 |
Tag: | Evolutionsstrategien; Evolutionäre Algorithmen; Genetische Algorithmen; Genetisches Programmieren Evolution Strategies; Evolutionary Algorithms; Genetic Algorithms; Genetic programming |
GND Keyword: | Soft Computing; Versuchsplanung; Evolutionsstrategie; Evolutionärer Algorithmus; Metaheuristik; Optimierung; Optimierungsproblem |
Contributor: | Bartz-Beielstein, Thomas |
Institutes and Central Facilities: | Fakultät für Informatik und Ingenieurwissenschaften (F10) / Fakultät 10 / Institut für Informatik |
Dewey Decimal Classification: | 000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik |
Open Access: | Open Access |
Licence (German): | ![]() |