Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)

Study of Quantum genetic algorithm based on mutative scale chaotic optimization

Authors
Hao Teng1, Baohua Zhao, Bingru Yang, Bin He
1School of Information Science , University of Jinan
Corresponding Author
Hao Teng
Available Online October 2007.
DOI
https://doi.org/10.2991/iske.2007.132How to use a DOI?
Keywords
GA, QGA, chaos optimization, mutative scale
Abstract

Aiming at the trouble of easy getting into local minimum in quantum genetic algorithm, this paper presents a new hybrid quantum genetic algorithm. Using the method of mutative scale chaos optimization strategy, chaotic search for optimization is implemented to the colony which has been processed one time with quantum genetic algorithm, which can lead rapid evolution of the colony. The method has advantages such as high searching efficiency, good computing precision and being convenient to use, etc. The test of typical function shows the performance of this kind of method is better than quantum genetic algorithm and genetic algorithm.

Copyright
© 2007, 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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Volume Title
Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
Series
Advances in Intelligent Systems Research
Publication Date
October 2007
ISBN
978-90-78677-04-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/iske.2007.132How to use a DOI?
Copyright
© 2007, 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  - CONF
AU  - Hao Teng
AU  - Baohua Zhao
AU  - Bingru Yang
AU  - Bin He
PY  - 2007/10
DA  - 2007/10
TI  - Study of Quantum genetic algorithm based on mutative scale chaotic optimization
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 770
EP  - 773
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.132
DO  - https://doi.org/10.2991/iske.2007.132
ID  - Teng2007/10
ER  -