In satellite system design, optimizing component layout is crucial for enhancing satellite performance. Recently, a research team led by Professor Wen Yao from the Defense Innovation Institute at the Chinese Academy of Military Science has made new progress in the field of 3D satellite component layout optimization. This innovative approach can rapidly provide engineers with high-quality component layout candidates, promising to improve spacecraft layout design efficiency and efficacy.
The research, published in the Chinese Journal of Aeronautics, introduces a new Satellite Three-dimensional Component Assignment and Layout Optimization (3D-SCALO) problem from practical engineering requirements, which takes the heat dissipation performance as the objective and considers the component 3D geometry constraints, system static stability constraints and special component position constraints.
"Traditional satellite layout optimization has heavily relied on manual methods, which are not only time-consuming but also prevent us from fully exploring the potential of the design space," said Yufeng Xia, the first author of the paper. "With increasingly complex and diverse satellite missions, developing efficient holistic satellite design methods has become an urgent challenge."
The 3D-SCALO problem is a challenging bilevel combinatorial optimization task involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer, with both influencing each other. To address this issue, the research team proposed a Mixed Integer Programming (MIP) model. It transformed the original bilevel optimization problem into a single-level one, where discrete component assignment optimization and continuous detailed position optimization were modelled into one comprehensive formulation, thus generating layout design in a single run and avoiding complex nested optimization iterations.
To address the challenge of modeling 3D geometric relationships within the MIP framework, researchers proposed a linearized 3D Phi-function method, which explicitly and effectively handles non-overlapping and safety distance constraints between cuboid components. On this basis, the Finite Rectangle Method (FRM) was further proposed to address the 3D geometric constraints between complex-shaped components, expanding the applicability of the method.
The research team verified the feasibility and effectiveness of the proposed model through two numerical examples and one real engineering case. Results demonstrated that the method could find globally optimal solutions within reasonable timeframes. In an engineering case involving 27 components across 5 modules, the model found the optimal solution in 193.5 seconds, fully demonstrating its applicability in complex engineering applications.
The research team states that they will continue in-depth research on the 3D-SCALO problem from the perspectives of problem modeling, analysis, and optimization algorithms to provide more efficient solutions, thereby advancing the intelligent design of spacecraft.
Other contributors include Xianqi Chen and Weien Zhou from the Defense Innovation Institute at the Chinese Academy of Military Science in Beijing, China; Zhijia Liu from DFH Satellite Co., Ltd. in Beijing, China; and Zhongneng Zhang from the College of Aerospace Science and Engineering at the National University of Defense Technology in Changsha, China.
Original Source
Yufeng XIA, Xianqi CHEN, Zhijia LIU, Weien ZHOU, Wen YAO, Zhongneng ZHANG. Mixed integer programming modeling for the satellite three-dimensional component assignment and layout optimization problem[J]. Chinese Journal of Aeronautics, 2025, https://doi.org/10.1016/j.cja.2025.103415
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