Designing Active Tether-Net Systems for Space Debris Capture with Graph-Learning-Aided Mixed-Combinatorial Optimization

In three linesActive tether-net system for space debris capture using Graph Neural Network (GNN) to jointly optimize net morphology, thruster masses of maneuverable units, and controller aiming points. GNN reduces mixed combinatorial nonlinear programming (MCNLP) to nonlinear programming (NLP) solved via Particle Swarm Optimization with gradient-based refinement, achieving faster convergence than direct MCNLP solving.

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