This Title All WIREs
How to cite this WIREs title:
WIREs Data Mining Knowl Discov
Impact Factor: 7.250

Evolutionary Algorithms

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract 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. WIREs Data Mining Knowl Discov 2014, 4:178–195. doi: 10.1002/widm.1124 This article is categorized under: Algorithmic Development > Spatial and Temporal Data Mining Fundamental Concepts of Data and Knowledge > Knowledge Representation
The evolutionary cycle, basic working scheme of all EAs. Common terms for describing ES are used, alternative terms (crossover, replacement) are added below.
[ Normal View | Magnified View ]
Illustration of (marginal) hypervolume.
[ Normal View | Magnified View ]
Crossover via subtree exchanging applied to two GP individuals (a) and (b), which are represented as binary trees. The first tree represents the S‐expression ‘(−(11 x))’, the second tree represents ‘(+(1 (* (x 3))))’. The dashed lines denote the positions, where crossover takes place. Two offspring are created: (c), which represents ‘(−(11 (* (x 3))))’ and (d), which represents the S‐expression ‘(+(1 x))’.
[ Normal View | Magnified View ]
Contour plot of f(x) and illustrating the effect of rotation on the function landscape.
[ Normal View | Magnified View ]

Browse by Topic

Fundamental Concepts of Data and Knowledge > Knowledge Representation
Algorithmic Development > Spatial and Temporal Data Mining

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts