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Results

Optimization Solver

See how Quantum Inspired Evolutionary Optimization Enhances Satellite Placement

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Challenges

Optimizing the placement of 12, 500, 1000, 4000 satellites across 4, 125, 250, 1000 targets while minimizing computational complexity for maximum coverage
Achieving faster convergence compared to classical optimization algorithms
Managing orbital constraints and inter-satellite dependencies efficiently

Results

QIEO improves optimization results

1.2x faster convergence

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Improved coverage

Maintained speed and stability at scale

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