A Dynamic Opposite Learning-Assisted Grey Wolf Optimizer

Yang Wang, Chengyu Jin, Qiang Li, Tinayu Hu, Yunlang Xu, Chao Chen, Yuqian Zhang, Zhile Yang
2022 Symmetry  
The grey wolf optimization (GWO) algorithm is widely utilized in many global optimization applications. In this paper, a dynamic opposite learning-assisted grey wolf optimizer (DOLGWO) was proposed to improve the search ability. Herein, a dynamic opposite learning (DOL) strategy is adopted, which has an asymmetric search space and can adjust with a random opposite point to enhance the exploitation and exploration capabilities. To validate the performance of DOLGWO algorithm, 23 benchmark
more » ... ns from CEC2014 were adopted in the numerical experiments. A total of 10 popular algorithms, including GWO, TLBO, PIO, Jaya, CFPSO, CFWPSO, ETLBO, CTLBO, NTLBO and DOLJaya were used to make comparisons with DOLGWO algorithm. Results indicate that the new model has strong robustness and adaptability, and has the significant advantage of converging to the global optimum, which demonstrates that the DOL strategy greatly improves the performance of original GWO algorithm.
doi:10.3390/sym14091871 fatcat:plgscdvigrenfjfaipoqj3qmzm