In this paper, in order to improve the search ability and adaptability of the seagull optimization algorithm, a multi-strategy collaborative improvement-based seagull optimization algorithm (MI-SOA) is proposed. Firstly, LogisticsTent chaotic mapping with is introduced to enhance the global search ability of the algorithm; secondly, the algorithm's search path is optimized by filtering out the superior and inferior solution locations through the inverse learning strategy to improve the quality of the solution; the algorithm combines the Lévy f...
