A scattering and repulsive swarm intelligence algorithm for solving global optimization problems
作者：
Highlights：
• Three swarm intelligence algorithms (RFA, SRFA and ESRFA) have been proposed.
• RFA accelerates the search process by avoiding unpromising regions.
• SRFA scatters weak solutions to new search regions to increase exploration.
• ESRFA conducts hovering, sharp-dive and best memory-guided search operations.
• They outperform other classical and state-of-the-art optimization methods.
摘要
•Three swarm intelligence algorithms (RFA, SRFA and ESRFA) have been proposed.•RFA accelerates the search process by avoiding unpromising regions.•SRFA scatters weak solutions to new search regions to increase exploration.•ESRFA conducts hovering, sharp-dive and best memory-guided search operations.•They outperform other classical and state-of-the-art optimization methods.
论文关键词：Optimization,Metaheuristic search algorithms,and Firefly algorithm
论文评审过程：Received 1 October 2016, Revised 29 April 2018, Accepted 2 May 2018, Available online 26 May 2018, Version of Record 4 June 2018.
论文官网地址：https://doi.org/10.1016/j.knosys.2018.05.002
