Joint Opposite Selection (JOS): A premiere joint of selective leading opposition and dynamic opposite enhanced Harris’ hawks optimization for solving single-objective problems
作者：
Highlights：
• Novel opposition-learning technique: Selective Leading Opposition (SLO).
• SLO dimensionally changes the close search agents’ distance.
• A well-match joint SLO and Dynamic Opposite (DO): Joint Opposite Selection (JOS).
• Random Jump Strategy of DO increases the exploration ability of algorithm.
• Promising performance improvement of HHO-JOS shown in CEC 2014 and CEC 2017.
摘要
•Novel opposition-learning technique: Selective Leading Opposition (SLO).•SLO dimensionally changes the close search agents’ distance.•A well-match joint SLO and Dynamic Opposite (DO): Joint Opposite Selection (JOS).•Random Jump Strategy of DO increases the exploration ability of algorithm.•Promising performance improvement of HHO-JOS shown in CEC 2014 and CEC 2017.
论文关键词：Harris’ Hawks Optimization (HHO),Joint Opposite Selection (JOS),Selective Opposition (SO),Dynamic Opposite (DO),Selection Leading Opposition (SLO),Nature-Inspired Optimization Algorithm
论文评审过程：Received 27 February 2021, Revised 19 July 2021, Accepted 28 September 2021, Available online 2 October 2021, Version of Record 18 October 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.116001
