Multi-objective grey wolf optimizer based on decomposition

作者：

Highlights：

• An enhanced algorithm for solving multi-objective optimization problems is proposed.

• The proposed algorithm improves the original Multi-Objective Grey Wolf Optimizer.

• This improvement is related to the decomposition of multi-objective problems.

• The proposed approach is evaluated on benchmark functions and real-world applications.

• Statistical analysis corroborates the good performance of the proposed algorithm.

摘要

•An enhanced algorithm for solving multi-objective optimization problems is proposed.•The proposed algorithm improves the original Multi-Objective Grey Wolf Optimizer.•This improvement is related to the decomposition of multi-objective problems.•The proposed approach is evaluated on benchmark functions and real-world applications.•Statistical analysis corroborates the good performance of the proposed algorithm.

论文关键词：Multi-objective evolutionary algorithms,Multi-objective grey wolf optimizer,Decomposition-based MOEAs

论文评审过程：Received 25 April 2018, Revised 5 September 2018, Accepted 1 December 2018, Available online 3 December 2018, Version of Record 5 December 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.003