Precomputed embeddings reduce the preprocessing overhead of a quantum-annealer-based Benders decomposition by about an order of magnitude on small transmission-network expansion problems, with no loss in solution quality.
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Performance enhancing of hybrid quantum-classical Benders approach for MILP optimization
Precomputed embeddings reduce the preprocessing overhead of a quantum-annealer-based Benders decomposition by about an order of magnitude on small transmission-network expansion problems, with no loss in solution quality.