Quantum-Enhanced Constraint Optimization (QCO)

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum-Enhanced Constraint Optimization (QCO) presents a novel approach to solving complex optimization problems by integrating quantum computing principles. This paper explores the potential of quantum algorithms to accelerate and enhance optimization processes, addressing inherent limitations of classical methods in handling intricate constraints. We detail the core mechanism of QCO, focusing on the utilization of quantum algorithms to overcome computational bottlenecks and achieve exponential increases in solution efficiency. The paper then discusses the theoretical implications, potential applications, and challenges associated with this paradigm shift in optimization. The core claim is that QCO offers a significant advancement in optimization, providing a pathway to more efficient and accurate solutions for a broad range of complex problems.

DOI: 10.5281/zenodo.22271917

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