期刊论文

Cui, Xingyue

Yin, FL (reprint author), Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116023, Peoples R China.

Chen, Zhe,Yin, Fuliang

2018-01-01

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS

SCIE

J

12

1

149-163

1875-6891

Monarch butterfly optimization; local search strategy; differential evolution; PID tuning; FIR filter design

Global optimization for nonlinear function is a challenging issue. In this paper, an improved monarch butterfly algorithm based on local search and differential evolution is proposed. Local search strategy is first embedded into original monarch butterfly optimization to enhance the searching capability. Then, differential evolution is incorporated with the aim of balancing the exploration and exploitation. To evaluate the performance of proposed algorithm, some widely-used benchmark functions are tested, and the experiment results show its significant superiority compared with other state-of-the-art methods. In addition, the proposed algorithm is applied to PID tuning and FIR filter design, the superiority of solving practical problems is verified.