A modified Covariance Matrix Adaptation Evolution Strategy with adaptive penalty function and restart for constrained optimization

作者：

Highlights：

• We introduce a modified Covariance Matrix Adaptation Evolution Strategy.

• Our CMA-ES is specifically designed for solving constrained optimization problems.

• The proposed method makes use of a restart mechanism and adaptive penalty function.

• This novel CMA-ES presents competitive results on a set of benchmark functions.

摘要

Highlights•We introduce a modified Covariance Matrix Adaptation Evolution Strategy.•Our CMA-ES is specifically designed for solving constrained optimization problems.•The proposed method makes use of a restart mechanism and adaptive penalty function.•This novel CMA-ES presents competitive results on a set of benchmark functions.

论文关键词：Constrained optimization,Covariance Matrix Adaptation Evolution Strategy,Adaptive penalty function

论文评审过程：Available online 21 June 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.06.032