A two-stage evolutionary strategy based MOEA/D to multi-objective problems

作者：

Highlights：

• A two-stage evolution strategy is proposed for solving multi-objective problem.

• The convergence and diversity should be balanced in multi-objective optimization.

• A local searching method can improve the diversity of solutions in the space.

• Experimental results have been presented by using statistical method.

摘要

•A two-stage evolution strategy is proposed for solving multi-objective problem.•The convergence and diversity should be balanced in multi-objective optimization.•A local searching method can improve the diversity of solutions in the space.•Experimental results have been presented by using statistical method.

论文关键词：Multi-objective optimization,Evolutionary algorithm,MOEA/D,Two-stage evolution,Pareto solution

论文评审过程：Received 23 February 2020, Revised 31 July 2020, Accepted 21 July 2021, Available online 27 July 2021, Version of Record 31 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115654