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Modified Selfish Herd Optimizer for Function Optimization

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, P. R. China

E-mail Address: nnzhaoms@126.com

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Yongli Wang

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, P. R. China

E-mail Address: yongliwang@njust.edu.cn

Corresponding author.

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Chang Liu

School of Intelligent Manufacturing, Yangzhou Polytechnic Institute, Yangzhou 225127, Jiangsu, P. R. China

E-mail Address: 18361821216@163.com

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Peng Hu

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, P. R. China

E-mail Address: hupeng1117@163.com

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Yanchao Li

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, P. R. China

E-mail Address: leeyc.gm@gmail.com

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Hao Li

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, P. R. China

E-mail Address: lihaosky_2008@126.com

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, and

Chi Yuan

School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, P. R. China

E-mail Address: yuanchi@njust.edu.cn

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https://doi.org/10.1142/S1469026820500030Cited by:1 (Source: Crossref)

Abstract

Selfish herd optimizer (SHO) is a new optimization algorithm. However, its optimization performance is not satisfactory. The main reason for this phenomenon is the weak global search ability of SHO. In this paper, in order to increase the global search ability of SHO, we add Levy-flight distribution strategy. To verify the performance of the proposed algorithm, we use 10 benchmark functions as test cases. Experiment results show that our algorithm is more competitive.

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