A hybrid layout optimization method based on genetic and differential evolution for Flat-panel (FP) microsatellite

Flat-panel (FP) satellites are a novel type of microsatellite configuration, and a hybrid algorithmic layout optimization method is studied in this paper to solve the problem of its large moment of inertia. The method is implemented by two-level algorithms of genetic and differential evolution, in which the genetic algorithm is used to realize the optimal allocation of components within different satellite modules to ensure the mass balance between satellite modules; the differential evolution algorithm further plans the positions of components within the modules and enables the satellite to obtain the optimal moment of inertia and layout scheme. Finally, the effectiveness of the proposed method is verified by the case of layout optimization of remote sensing satellites.