Frontiers in Energy Research (Jan 2023)

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

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

DOI
https://doi.org/10.3389/fenrg.2022.1030034
Journal volume & issue
Vol. 10

Abstract

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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.

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