Quantum-Inspired Optimization for Constraint Satisfaction Problems (QISCP)

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces Quantum-Inspired Optimization for Constraint Satisfaction Problems (QISCP), a novel optimization algorithm inspired by quantum mechanics, designed to enhance performance in large-scale constraint satisfaction problems. We propose a framework where constraint satisfaction is modeled as a quantum state evolution, leveraging quantum entanglement to facilitate efficient exploration of the solution space. The core mechanism involves mapping the problem onto a quantum state, allowing for faster and more nuanced optimization compared to classical approaches. We demonstrate the effectiveness of this approach through simulations and preliminary analysis, showing significant improvements in solution quality and scalability.

DOI: 10.5281/zenodo.22315528

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