Constrained multi-objective evolutionary algorithm with an improved two-archive strategy

作者：

Highlights：

• An improved two-archive based EA is proposed for the CMOPs.

• New fitness evaluation strategies are designed for the two archives.

• An enhanced mating selection strategy is developed.

• Results demonstrate the superiority of our approach to other CMOEAs.

摘要

•An improved two-archive based EA is proposed for the CMOPs.•New fitness evaluation strategies are designed for the two archives.•An enhanced mating selection strategy is developed.•Results demonstrate the superiority of our approach to other CMOEAs.

论文关键词：Constrained multi-objective optimization,Evolutionary algorithm,Two archive,Fitness evaluation,Mating selection

论文评审过程：Received 2 July 2021, Revised 31 March 2022, Accepted 1 April 2022, Available online 8 April 2022, Version of Record 18 April 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2022.108732