An improved monkey algorithm with dynamic adaptation

作者：

Highlights：

• Chaotic search method is utilized to generate the random numbers in MA.

• Step length is adjusted dynamically according to evolutionary speed factor.

• Eyesight and watch times grow adaptively as the aggregation degree increases.

• Somersault distance increases with the increase of the aggregation degree.

• Modified algorithm improves search ability of MA and has an advantage of robustness.

摘要

•Chaotic search method is utilized to generate the random numbers in MA.•Step length is adjusted dynamically according to evolutionary speed factor.•Eyesight and watch times grow adaptively as the aggregation degree increases.•Somersault distance increases with the increase of the aggregation degree.•Modified algorithm improves search ability of MA and has an advantage of robustness.

论文关键词：Monkey algorithm,Dynamic adaptation,Chaotic search,Evolutionary speed,Aggregation degree

论文评审过程：Available online 26 August 2013.

论文官网地址：https://doi.org/10.1016/j.amc.2013.07.067