Title: Quantum-Enhanced Constraint Programming for Complex Optimization

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

Quantum-enhanced constraint programming (QCP) presents a novel approach to tackling complex optimization problems by integrating quantum algorithms into the constraint programming framework. This paper explores the potential of quantum annealing and quantum approximate optimization algorithms (QAOA) to accelerate solution exploration and enhance the ability to find optimal solutions for challenging problems. We detail the core mechanism, highlighting its advantages over classical methods in navigating high-dimensional constraint spaces and potential for improved performance in diverse optimization scenarios. The study focuses on demonstrating the efficacy of this technique through illustrative examples, showcasing the benefits of leveraging quantum resources for complex optimization.

DOI: 10.5281/zenodo.22638737

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