Differential evolution with dynamic combination based mutation operator and two-level parameter adaptation strategy

作者：

Highlights：

• Combining elite individual and optimal individual to propose a new mutation operator.

• Combining a macro parameter and a micro parameter to adjust the core parameters.

• Relationship between operator and parameter is considered when designing algorithm.

• Comparison results show that the proposed DCDE algorithm has superior performance.

摘要

•Combining elite individual and optimal individual to propose a new mutation operator.•Combining a macro parameter and a micro parameter to adjust the core parameters.•Relationship between operator and parameter is considered when designing algorithm.•Comparison results show that the proposed DCDE algorithm has superior performance.

论文关键词：Differential evolution,Mutation operator,Two-level parameter,Numerical optimization

论文评审过程：Received 16 August 2020, Revised 28 June 2021, Accepted 24 November 2021, Available online 18 December 2021, Version of Record 22 December 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116298