Affiliation:
1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, P. R. China
2. School of Intelligent Manufacturing, Yangzhou Polytechnic Institute, Yangzhou 225127, Jiangsu, P. R. China
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.
Funder
National Natural Science Foundation of China
Fundamental Research Fund for the Central Universities
Nanjing Science and Technology Development Plan Project
“13th Five-Year” equipment field fund
China Academy of Engineering Consulting Research
National Social Science Foundation
State Grid Technology Project
China Scholarship Council
Publisher
World Scientific Pub Co Pte Lt
Subject
Computer Science Applications,Theoretical Computer Science,Software
Cited by
2 articles.
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