A ranking-based adaptive cuckoo search algorithm for unconstrained optimization

作者：

Highlights：

• A ranking-based adaptive cuckoo search algorithm is proposed.

• A ranking-based mutation strategy is developed to enhance the exploitation ability.

• The crossover operation is used to preserve some good elements from being changed.

• A replacement strategy is designed to avoid stagnation.

• RACS exhibits superior performance when solving various test problems.

摘要

•A ranking-based adaptive cuckoo search algorithm is proposed.•A ranking-based mutation strategy is developed to enhance the exploitation ability.•The crossover operation is used to preserve some good elements from being changed.•A replacement strategy is designed to avoid stagnation.•RACS exhibits superior performance when solving various test problems.

论文关键词：Cuckoo search,Adaptive ranking selection,Unconstrained optimization,Parameter identification,Fractional-order chaotic systems

论文评审过程：Received 24 June 2021, Revised 31 March 2022, Accepted 26 April 2022, Available online 14 May 2022, Version of Record 25 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117428