An efficient double adaptive random spare reinforced whale optimization algorithm

作者：

Highlights：

• This paper proposes an enhanced whale optimizer (WOA) for global search.

• Strategy of random replacement is created to enhance the convergence speed of WOA.

• Strategy of double adaptive weight is introduced to improve the ability of global search of WOA.

• The excellent performance is validated on benchmark problems and engineering problems.

摘要

•This paper proposes an enhanced whale optimizer (WOA) for global search.•Strategy of random replacement is created to enhance the convergence speed of WOA.•Strategy of double adaptive weight is introduced to improve the ability of global search of WOA.•The excellent performance is validated on benchmark problems and engineering problems.

论文关键词：Whale optimization,Engineering design,Swarm-intelligence,Global optimization,Nature-inspired computing

论文评审过程：Received 8 June 2019, Revised 28 September 2019, Accepted 10 October 2019, Available online 13 October 2019, Version of Record 23 May 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.113018