A feedback-based prediction strategy for dynamic multi-objective evolutionary optimization

作者：

Highlights：

• A feedback-based prediction strategy based DMOEA namely MOEA/D-FPS is proposed.

• A new method for decision variable classification is introduced.

• Correction feedback and effectiveness feedback mechanisms are suggested.

• MOEA/D-FPS is efficient at solving various dynamic multi-objective problems.

摘要

•A feedback-based prediction strategy based DMOEA namely MOEA/D-FPS is proposed.•A new method for decision variable classification is introduced.•Correction feedback and effectiveness feedback mechanisms are suggested.•MOEA/D-FPS is efficient at solving various dynamic multi-objective problems.

论文关键词：Dynamic multi-objective optimization,Evolutionary algorithm,Variable classification,Step size exploration,Feedback

论文评审过程：Received 23 November 2019, Revised 6 January 2021, Accepted 7 January 2021, Available online 13 January 2021, Version of Record 6 February 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114594