Improved grasshopper optimization algorithm using opposition-based learning

作者：

Highlights：

• A modified GOA is proposed based on opposite-based learning strategy (OBLGOA).

• OBLGOA is evaluated using 23 benchmark problems and four engineering problems.

• The results were superior to those of well-known algorithms in optimization domain.

摘要

•A modified GOA is proposed based on opposite-based learning strategy (OBLGOA).•OBLGOA is evaluated using 23 benchmark problems and four engineering problems.•The results were superior to those of well-known algorithms in optimization domain.

论文关键词：Grasshopper optimization algorithm,Opposition-based learning,Benchmark functions,Engineering problems optimization

论文评审过程：Received 9 November 2017, Revised 9 June 2018, Accepted 10 June 2018, Available online 15 June 2018, Version of Record 26 June 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.06.023