Quantum-Inspired Optimization Algorithms for Constraint Satisfaction Problems

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum-inspired optimization algorithms represent a novel approach to addressing constraint satisfaction problems (CSPs) by mimicking the phenomena observed in quantum systems. This paper explores the potential of adapting quantum principles – specifically superposition and entanglement – to enhance the search process within CSPs, aiming to overcome the limitations of classical algorithms. We detail the core mechanism of this design, focusing on how the algorithms leverage quantum concepts to explore a wider range of potential solutions and improve overall performance. The paper presents a comprehensive analysis of the proposed framework and its expected impact on solving complex CSPs.

DOI: 10.5281/zenodo.22291102

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