Quantum-Inspired Constraint Propagation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the potential of quantum-inspired algorithms to significantly accelerate the solution of complex constraint satisfaction problems (CSPs). Traditional CSP solvers often struggle with large instances, requiring substantial computational resources and time. We propose a novel approach that integrates quantum-inspired search techniques into the constraint propagation process, aiming to identify and explore solution spaces more efficiently. The core mechanism centers around the utilization of quantum-inspired algorithms to guide the search towards promising regions of the solution space, reducing the search space and improving solution finding speed. We demonstrate the efficacy of this approach through theoretical analysis and preliminary experiments on several challenging CSPs. The results demonstrate a substantial reduction in computational time compared to conventional methods, highlighting the potential of this quantum-inspired strategy.

DOI: 10.5281/zenodo.22190777

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