Cooperative meta-heuristic algorithms for global optimization problems
作者：
Highlights：
• Developed a global optimization approach using cooperative meta-heuristic methods.
• The proposed method inspired from the natural selection theory.
• DE, GWO, WOA, SSA, SCA, and SOS are used to build the proposed method.
• Three variants of proposed are developed based on strategy of updating solutions.
• Results of proposed method compared with other methods using CEC2014 and CEC2017.
摘要
•Developed a global optimization approach using cooperative meta-heuristic methods.•The proposed method inspired from the natural selection theory.•DE, GWO, WOA, SSA, SCA, and SOS are used to build the proposed method.•Three variants of proposed are developed based on strategy of updating solutions.•Results of proposed method compared with other methods using CEC2014 and CEC2017.
论文关键词：Meta-heuristics (MH),Natural selection theory (NLT),Global optimization,Cooperative meta-heuristics
论文评审过程：Received 9 October 2019, Revised 3 December 2020, Accepted 22 February 2021, Available online 4 March 2021, Version of Record 3 April 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.114788
