Dynamic group optimization algorithm with a mean–variance search framework
作者：
Highlights：
• The proportioned mean solution generator can avoid fast shrinkage of search space.
• Two significant difference individuals are perturbed to provide more useful information.
• Population diversity is increased.
• A lifespan selection operator is used to enhance the ability to avoid local optimum.
• Comparative results of engineering problems in welded beam design show the promise of our algorithms for real-world applications.
摘要
•The proportioned mean solution generator can avoid fast shrinkage of search space.•Two significant difference individuals are perturbed to provide more useful information.•Population diversity is increased.•A lifespan selection operator is used to enhance the ability to avoid local optimum.•Comparative results of engineering problems in welded beam design show the promise of our algorithms for real-world applications.
论文关键词：Metaheuristic algorithm,Dynamic group optimization algorithm,Mean–variance search framework
论文评审过程：Received 5 July 2020, Revised 1 June 2021, Accepted 10 June 2021, Available online 15 June 2021, Version of Record 20 June 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115434
