Selective Opposition based Grey Wolf Optimization
作者：
Highlights：
• Application of opposition-based learning on weak wolves.
• Proposed method is called Selective Opposition based Grey Wolf Optimization.
• Improving exploration ability of the method sans affecting its convergence rate.
• Evaluation of proposed method on 23 benchmark functions.
• Proposed method outperforms contemporary optimization methods.
摘要
•Application of opposition-based learning on weak wolves.•Proposed method is called Selective Opposition based Grey Wolf Optimization.•Improving exploration ability of the method sans affecting its convergence rate.•Evaluation of proposed method on 23 benchmark functions.•Proposed method outperforms contemporary optimization methods.
论文关键词：Grey Wolf Optimizer,Opposition-based Learning,Spearman's coefficient,Selective opposition
论文评审过程：Received 13 October 2019, Revised 13 March 2020, Accepted 14 March 2020, Available online 17 March 2020, Version of Record 8 April 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113389
