AUTHOR=Huang Xuyong , Tang Biao , Zhu Mengmeng , Ma Yutang , Ma Xianlong , Tang Lijun , Wang Xin , Zhu Dongdong 

TITLE=Like-attracts-like optimizer-based video robotics clustering control design for power device monitoring and inspection

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.1030034

DOI=10.3389/fenrg.2022.1030034

ISSN=2296-598X

ABSTRACT=This paper proposes a novel meta-heuristic algorithm called like-attracts-like optimizer (LALO). It is inspired by that an excellent person (i.e., a high-quality solution) easily attracts the like-minded persons to approach him or her. This LALO algorithm is an important inspiration for video robotics cluster control. Firstly, the searching individuals are dynamically divided into multiple clusters by a growing neural gas network according to their positions, in which the topological relations between different clusters can also be determined. Secondly, each individual will approach a better individual from its superordinate cluster and the adjacent clusters. The performance of LALO is evaluated on unimodal benchmark functions compared with various well-known meta-heuristic algorithms, which reveals that it is competitive for some optimizations.