Quantum-Inspired Optimization of Large-Scale Scheduling Problems

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper investigates the application of quantum-inspired optimization algorithms to the resolution of large-scale scheduling problems. The core premise is that techniques inspired by quantum mechanics, specifically quantum annealing, can provide efficient solutions to these complex problems. The approach involves mapping the scheduling problem onto a quantum annealer model, leveraging the quantum tunneling effect to effectively explore the solution space and converge towards optimal schedules. We present a framework for this mapping and discuss the potential advantages in terms of speed and scalability compared to traditional classical optimization methods. The research contributes to the growing intersection of quantum computing concepts with operations research, offering a novel approach to tackling significant scheduling challenges.

DOI: 10.5281/zenodo.22316774

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