A multi-objective elitist feedback teaching–learning-based optimization algorithm and its application

作者：

Highlights：

• A novel multi-objective evolutionary algorithm (MEFTO) is developed.

• The developed algorithm is evaluated on a series of benchmark functions.

• The performance of the MEFTO is demonstrated using various metrics.

• The developed algorithm is applied to solve three constrained engineering problem.

摘要

•A novel multi-objective evolutionary algorithm (MEFTO) is developed.•The developed algorithm is evaluated on a series of benchmark functions.•The performance of the MEFTO is demonstrated using various metrics.•The developed algorithm is applied to solve three constrained engineering problem.

论文关键词：Multi-objective optimization,Teaching–learning-based optimization,Feedback phase,Non-dominated sorting,Elitism strategy

论文评审过程：Received 1 March 2020, Revised 5 May 2021, Accepted 22 September 2021, Available online 14 October 2021, Version of Record 23 October 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115972