Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)

A Novel Hybrid Bat Algorithm Based on Tent Map and Mutation Operator

Authors
Kairong Zhang, Xueqin Tang, Yaohui Zhang, Jian Gu
Corresponding Author
Kairong Zhang
Available Online October 2016.
DOI
https://doi.org/10.2991/ceie-16.2017.31How to use a DOI?
Keywords
Bat Algorithm; Local Optimum; Tent Map; Genetic Algorithm; Mutation Operator
Abstract
Standard bat algorithm is easy to fall into local optimum to handle complex functions with high- dimension. This paper proposes a hybrid chaotic mutation bat algorithm handling local convergence. The chaotic variables and mutation operator are introduced to bat algorithm to enhance its global search ability. The simulation experimental results based on typical test functions show that the improved algorithm can effectively improve the global optimization ability of the bat algorithm and significantly improve the accuracy of the algorithm optimization and convergence efficiency.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
978-94-6252-312-8
ISSN
2352-5401
DOI
https://doi.org/10.2991/ceie-16.2017.31How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Kairong Zhang
AU  - Xueqin Tang
AU  - Yaohui Zhang
AU  - Jian Gu
PY  - 2016/10
DA  - 2016/10
TI  - A Novel Hybrid Bat Algorithm Based on Tent Map and Mutation Operator
BT  - Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)
PB  - Atlantis Press
SP  - 239
EP  - 246
SN  - 2352-5401
UR  - https://doi.org/10.2991/ceie-16.2017.31
DO  - https://doi.org/10.2991/ceie-16.2017.31
ID  - Zhang2016/10
ER  -