International Journal of Computational Intelligence Systems

Volume 6, Issue 1, January 2013, Pages 47 - 63

Parameters control in GAs for dynamic optimization

Authors
Khalid Jebari, Abdelaziz Bouroumi, Aziz Ettouhami
Corresponding Author
Khalid Jebari
Received 1 February 2012, Accepted 20 August 2012, Available Online 2 January 2013.
DOI
10.1080/18756891.2013.754172How to use a DOI?
Keywords
Genetic Algorithms, Unsupervised Learning, Fuzzy Clustering, Dynamic Optimization, Evolutionary Algorithms, Fitness Sharing, Multi-modal function optimization, Generalized dynamic benchmark generator (GDBG)
Abstract

The Control of Genetic Algorithms parameters allows to optimize the search process and improves the performance of the algorithm. Moreover it releases the user to dive into a game process of trial and failure to find the optimal parameters.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
6 - 1
Pages
47 - 63
Publication Date
2013/01/02
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2013.754172How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Khalid Jebari
AU  - Abdelaziz Bouroumi
AU  - Aziz Ettouhami
PY  - 2013
DA  - 2013/01/02
TI  - Parameters control in GAs for dynamic optimization
JO  - International Journal of Computational Intelligence Systems
SP  - 47
EP  - 63
VL  - 6
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.754172
DO  - 10.1080/18756891.2013.754172
ID  - Jebari2013
ER  -