Friday 22nd of September 2017
 

A new hybrid artificial bee colony algorithm for global optimization


Xiangyu Kong, Sanyang Liu and Zhen Wang

To further improve the performance of artificial bee colony algorithm (ABC), a new hybrid ABC (HABC) for global optimization is proposed via exploring six initialization methods. Furthermore, to balance the exploration and exploitation abilities, a new search mechanism is also developed. The algorithms are applied to 27 benchmark functions with various dimensions to verify its performance. Numerical results demonstrate that the proposed algorithms outperforms the ABC in global optimization problems, especially the HABC algorithm with random initialization and HABCO algorithm with orthogonal initialization.

Keywords: Artificial bee colony algorithm, Initialization methods, Search mechanism, Differential evolution.

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ABOUT THE AUTHORS

Xiangyu Kong
Department of Applied Mathematics, Xidian University

Sanyang Liu
Department of Applied Mathematics, Xidian University

Zhen Wang
Institute of Information and System Computation Science, Beifang University of Nationalities


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