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Quantum Machine Learning
Quantum Optimization
Accelerating Extended Benders Decomposition with Quantum-Classical Hybrid Solver
arXiv
Authors: Takuma Yoshihara, Masayuki Ohzeki
Year
2025
Paper ID
51865
Status
Preprint
Abstract Read
~2 min
Abstract Words
94
Citations
N/A
Abstract
We propose a quantum-classical hybrid method for solving large-scale mixed-integer quadratic problems (MIQP). Although extended Benders decomposition is effective for MIQP, its master problem which handles the integer and quadratic variables often becomes a computational bottleneck. To address this challenge, we integrate the D-Wave CQM solver into the decomposition framework to solve the master problem directly. Our results show that this hybrid approach efficiently yields near-optimal solutions and, for certain problem instances, achieves exponential speedups over the leading commercial classical solver. These findings highlight a promising computational strategy for tackling complex mixed-integer optimization problems.
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- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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- We propose a quantum-classical hybrid method for solving large-scale mixed-integer quadratic problems (MIQP).
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