Quantum-Inspired Algorithm for Optimization

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

Quantum-inspired algorithms are emerging as a promising alternative to classical optimization techniques, particularly for complex problem domains. This paper introduces a novel quantum-inspired algorithm designed to leverage the principles of superposition and entanglement to enhance search and solution efficiency. We explore the potential of these concepts to represent and manipulate problem states, offering a fundamentally different approach to optimization. The algorithm's core mechanism centers around creating a quantum-like state space, enabling efficient exploration of the solution space. This work presents a preliminary analysis of the algorithm's potential for exponential speedups, although further investigation and validation are necessary.

DOI: 10.5281/zenodo.22324562

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