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Title: Quantum-Inspired Constraint Programming for Unconstrained Optimization

Jincheng Zhang

Published Sep 6, 2026• 0 citations
Publisher

Abstract

Quantum-inspired constraint programming (QICP) aims to leverage the principles of quantum mechanics – superposition and entanglement – to enhance the exploration of complex optimization problems. This paper introduces a novel constraint programming language, Quantum-Inspired Constraint Programming (QICP), built upon the concept of quantum-inspired operators. We demonstrate the effectiveness of this approach in solving optimization problems with high-dimensional constraints, proposing a new mechanism for guiding the search process towards optimal solutions. Quantum-inspired operators are designed to mimic the behavior of quantum states, facilitating a more efficient and robust exploration of the search space. The paper explores the theoretical foundations and practical implementation of QICP, showcasing its potential to surpass existing constraint programming techniques in certain scenarios. The core claim is that QICP offers a fundamentally new paradigm for solving optimization problems, particularly those exhibiting high-dimensional constraints and complex multi-constrained scenarios, by incorporating quantum-inspired mechanics.

DOI
10.5281/zenodo.22481929

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