Mutation-driven grey wolf optimizer with modified search mechanism

作者：

Highlights：

• A new mutation-driven modified grey wolf optimizer (GWO) is proposed.

• Search mechanism of GWO is modified using multi-parent crossover.

• The control parameter ‘a’ is redefined to be non-linearly decreasing with iterations.

• Levy-flight based mutation scheme is used to enhance the global search ability.

摘要

•A new mutation-driven modified grey wolf optimizer (GWO) is proposed.•Search mechanism of GWO is modified using multi-parent crossover.•The control parameter ‘a’ is redefined to be non-linearly decreasing with iterations.•Levy-flight based mutation scheme is used to enhance the global search ability.

论文关键词：Grey wolf optimizer,Exploration and exploitation,Mutation,Swarm intelligence

论文评审过程：Received 7 July 2021, Revised 21 December 2021, Accepted 23 December 2021, Available online 12 January 2022, Version of Record 21 January 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116450