A simple two-stage evolutionary algorithm for constrained multi-objective optimization

作者：

Highlights：

• A simple and generic two-stage framework is proposed for CMOPs.

• C-TSEA is presented based on the framework to effectively solve CMOPs.

• Fifty-seven CMOPs are chosen to extensively evaluate its performance.

• C-TSEA gets better or competitive results compared with other methods.

摘要

•A simple and generic two-stage framework is proposed for CMOPs.•C-TSEA is presented based on the framework to effectively solve CMOPs.•Fifty-seven CMOPs are chosen to extensively evaluate its performance.•C-TSEA gets better or competitive results compared with other methods.

论文关键词：Constrained multi-objective optimization,Evolutionary algorithm,Two-stage framework,Constrained Pareto front

论文评审过程：Received 1 April 2021, Revised 20 May 2021, Accepted 25 June 2021, Available online 27 June 2021, Version of Record 28 June 2021.

论文官网地址：https://doi.org/10.1016/j.knosys.2021.107263