Opposition-based moth swarm algorithm
作者：
Highlights：
• An improved MSA algorithm called OBMSA is proposed for global optimization.
• The proposed method combined the MSA with opposition-based learning.
• The OBMSA is tested over mathematical benchmark functions.
• The OBMSA is tested over engineering optimization problems.
• Experiments and comparisons support the better performance of OBMSA compared to other methods.
摘要
•An improved MSA algorithm called OBMSA is proposed for global optimization.•The proposed method combined the MSA with opposition-based learning.•The OBMSA is tested over mathematical benchmark functions.•The OBMSA is tested over engineering optimization problems.•Experiments and comparisons support the better performance of OBMSA compared to other methods.
论文关键词：Moth swarm algorithm,Opposition-based learning,Optimization techniques,Metaheuristics
论文评审过程：Received 30 December 2019, Revised 24 November 2020, Accepted 23 June 2021, Available online 27 June 2021, Version of Record 13 July 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115481
