A selection method for evolutionary algorithms based on the Golden Section

作者：

Highlights：

• Nature has developed patterns and processes with interesting characteristics.

• One of the most famous patterns present in the nature is the Golden Section (GS).

• In this paper, a new selection method for evolutionary computation algorithms is introduced.

• In the proposed approach, the population is segmented in several groups according to the GS.

• Numerical simulations show that the proposed method achieves a good performance.

摘要

•Nature has developed patterns and processes with interesting characteristics.•One of the most famous patterns present in the nature is the Golden Section (GS).•In this paper, a new selection method for evolutionary computation algorithms is introduced.•In the proposed approach, the population is segmented in several groups according to the GS.•Numerical simulations show that the proposed method achieves a good performance.

论文关键词：Evolutionary algorithms,Golden Section,Selection methods,Genetic algorithms (GA),Evolutionary strategies (ES),Genetic Programming (GP),Evolutionary computation

论文评审过程：Received 5 March 2017, Revised 5 March 2018, Accepted 31 March 2018, Available online 9 April 2018, Version of Record 14 April 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.064