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Quantum-Inspired Constraint Satisfaction with Adaptive Search Patterns

Jincheng Zhang

Published Aug 31, 2026• 0 citations
Publisher

Abstract

Quantum-inspired constraint satisfaction (CSI) solvers have been proposed as a promising alternative to traditional search algorithms. This paper investigates a novel approach that integrates quantum-inspired search patterns within a constraint satisfaction framework. We introduce a dynamic search strategy that adapts to the problem's state, leveraging the potential of quantum mechanics to accelerate solution exploration and enhance robustness. The core mechanism revolves around identifying promising solutions using quantum-inspired search, while concurrently incorporating a probabilistic framework to mitigate the effects of local optima. The study demonstrates improved performance on a suite of benchmark problems, showcasing the potential of this approach to address limitations in conventional CSI methods.

DOI
10.5281/zenodo.22199868

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