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=10 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=

A new meta-heuristic algorithm called like-attracts-like optimizer (LALO) is proposed in this article. It is inspired by the fact that an excellent person (i.e., a high-quality solution) easily attracts like-minded people to approach him or her. This LALO algorithm is an important inspiration for video robotics cluster control. First, 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. Second, each individual will approach a better individual from its superordinate cluster and the adjacent clusters. The performance of LALO is evaluated based on unimodal benchmark functions compared with various well-known meta-heuristic algorithms, which reveals that it is competitive for some optimizations.