Quantum-Inspired Optimization Algorithms for Complex Systems

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum-Inspired Optimization Algorithms (QIOA) represent a novel approach to optimization, drawing inspiration from the principles of quantum mechanics – specifically superposition and entanglement – to enhance the exploration of solution spaces for complex systems. This paper introduces QIOA, a new algorithm designed to address challenges inherent in optimization across diverse fields, including robotics, materials science, and financial modeling. The core mechanism centers on translating complex, multi-dimensional problems into a quantum-inspired framework, enabling efficient traversal of solution spaces and facilitating the discovery of optimal configurations. We present a detailed theoretical analysis, illustrating the algorithm's effectiveness through simulations and preliminary experimental validation. The paper concludes with a discussion of the potential impact of QIOA on complex system optimization, highlighting its advantages and future research directions.

DOI: 10.5281/zenodo.22246786

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