Immune Generalized Differential Evolution for dynamic multi-objective environments: An empirical study

作者：

Highlights：

• A Dynamic Multiobjective Evolutionary Algorithm (Immune GDE3) is empirically analyzed.

• Proximity to the Pareto front and distribution of obtained solutions are explored.

• The role immune response involved in GDE3 is analyzed.

• An adaptation of a binary metric to evaluate the performance of DMOEAs is presented.

• Immune GDE3 was very promising for dealing with DMOPs.

摘要

•A Dynamic Multiobjective Evolutionary Algorithm (Immune GDE3) is empirically analyzed.•Proximity to the Pareto front and distribution of obtained solutions are explored.•The role immune response involved in GDE3 is analyzed.•An adaptation of a binary metric to evaluate the performance of DMOEAs is presented.•Immune GDE3 was very promising for dealing with DMOPs.

论文关键词：GDE3,Artificial immune system,DMOPs,Immune response

论文评审过程：Received 18 April 2017, Revised 28 November 2017, Accepted 29 November 2017, Available online 2 December 2017, Version of Record 17 January 2018.

论文官网地址：https://doi.org/10.1016/j.knosys.2017.11.037