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

DOI

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.

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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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  - 10.2991/ceie-16.2017.31
ID  - Zhang2016/10
ER  -