An improved MOEA/D algorithm for bi-objective optimization problems with complex Pareto fronts and its application to structural optimization

作者：

Highlights：

• An improved MOEA/D (iMOEA/D) is proposed for bi-objective optimization problems with complex Pareto fronts.

• An adaptive replacement strategy and a stopping criterion are integrated into iMOEA/D.

• iMOEA/D is evaluated using seven complicated benchmark functions and three practical problems.

• iMOEA/D generally outperforms MOEA/D and NSGA-II in both benchmark functions and real applications.

摘要

•An improved MOEA/D (iMOEA/D) is proposed for bi-objective optimization problems with complex Pareto fronts.•An adaptive replacement strategy and a stopping criterion are integrated into iMOEA/D.•iMOEA/D is evaluated using seven complicated benchmark functions and three practical problems.•iMOEA/D generally outperforms MOEA/D and NSGA-II in both benchmark functions and real applications.

论文关键词：Multi-objective evolutionary algorithm (MOEA),Multi-objective evolutionary algorithm based on decomposition (MOEA/D),Complicated Pareto fronts (PFs),Structural optimization,Truss structures

论文评审过程：Received 8 June 2017, Revised 22 September 2017, Accepted 23 September 2017, Available online 28 September 2017, Version of Record 6 October 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.09.051