Exploratory differential ant lion-based optimization

作者：

Highlights：

• An enhanced ant lion optimizer is proposed to solve complex optimization tasks.

• Opposition-based learning and differential evolution are introduced to ant lion optimizer.

• The proposed method can efficiently solve the constrained engineering problem.

摘要

•An enhanced ant lion optimizer is proposed to solve complex optimization tasks.•Opposition-based learning and differential evolution are introduced to ant lion optimizer.•The proposed method can efficiently solve the constrained engineering problem.

论文关键词：Ant lion optimizer,Mathematical benchmark tasks,Practical constrained mathematical modeling

论文评审过程：Received 22 February 2019, Revised 8 March 2020, Accepted 9 May 2020, Available online 19 May 2020, Version of Record 17 June 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113548