A hybridized multi-algorithm strategy for engineering optimization problems
作者：
Highlights：
• A new self-adaptive multi-hybrid algorithm (MHA) is proposed.
• A new stagnation phase is added to overcome local optima stagnation problem.
• The algorithm is successfully tested on well-known CEC 2005 and CEC 2014 benchmark problems.
• MHA is used for real world optimization of Multi-level image thresholding problem.
• Experiments and statistical results show that MHA is efficient and effective.
摘要
•A new self-adaptive multi-hybrid algorithm (MHA) is proposed.•A new stagnation phase is added to overcome local optima stagnation problem.•The algorithm is successfully tested on well-known CEC 2005 and CEC 2014 benchmark problems.•MHA is used for real world optimization of Multi-level image thresholding problem.•Experiments and statistical results show that MHA is efficient and effective.
论文关键词：Multi-hybrid algorithm,Numerical optimization,Adaptive properties,Naked mole rat algorithm,Image thresholding
论文评审过程：Received 30 August 2020, Revised 11 November 2020, Accepted 17 January 2021, Available online 9 February 2021, Version of Record 15 February 2021.
论文官网地址：https://doi.org/10.1016/j.knosys.2021.106790
