DocumentCode
1050243
Title
Evolutionary algorithms for real world applications [Application Notes]
Author
Bäck, Thomas ; Emmerich, M. ; Shir, O.M.
Author_Institution
Leiden Univ., Leiden
Volume
3
Issue
1
fYear
2008
fDate
2/1/2008 12:00:00 AM
Firstpage
64
Lastpage
67
Abstract
In this section, we will report on three applications of evolutionary algorithms (EA) in real world parameter optimization. These applications show how the principles, such as robustness and representation independence, make it possible to extend the scope of optimization algorithms available so far and find answers to problems where classical solution methods fail.Evolutionary algorithms are today a state-of-the-art methodology in solving hard optimization problems, and are regularly being used in industries such as automotive and aerospace. In fact, these algorithms have revolutionized the way hard problems are being solved today. The pioneers of evolutionary computation, including Larry Fogel as one the key founders of the field, have been laying the foundations with their creativity and visionary approach toward science.
Keywords
chemical engineering computing; evolutionary computation; medical image processing; quantum computing; chemical engineering; evolutionary algorithm; medical image processing; parameter optimization; quantum control; state-of-the-art methodology; Computational intelligence; Evolutionary computation; Gaussian distribution; Genetic algorithms; Genetic mutations; Genetic programming; Size control; Stochastic processes; Storms; Writing;
fLanguage
English
Journal_Title
Computational Intelligence Magazine, IEEE
Publisher
ieee
ISSN
1556-603X
Type
jour
DOI
10.1109/MCI.2007.913378
Filename
4442256
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