A modified particle swarm optimization using adaptive strategy

作者：

Highlights：

• A chaos-based non-linear inertia weight is used to balance capacities better.

• Stochastic and mainstream learning strategies are devised to enhance diversity.

• An adaptive position updating strategy further adjusts balance.

• A terminal replacement mechanism is adopted to enhance convergence precise.

摘要

•A chaos-based non-linear inertia weight is used to balance capacities better.•Stochastic and mainstream learning strategies are devised to enhance diversity.•An adaptive position updating strategy further adjusts balance.•A terminal replacement mechanism is adopted to enhance convergence precise.

论文关键词：Particle swarm optimization,Chaos,Stochastic learning,Mainstream learning,Adaptive strategy

论文评审过程：Received 12 August 2019, Revised 31 December 2019, Accepted 3 March 2020, Available online 4 March 2020, Version of Record 13 March 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113353