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arxiv: 2402.17520 · v2 · pith:MIDMAWYGnew · submitted 2024-02-27 · 🪐 quant-ph

Quantum Computing in Logistics and Supply Chain Management an Overview

classification 🪐 quant-ph
keywords quantumcomputingannealingchainlogisticsoptimisationoverviewpotential
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The work explores the integration of quantum computing into logistics and supply chain management, emphasising its potential for use in complex optimisation problems. The discussion introduces quantum computing principles, focusing on quantum annealing and gate-based quantum computing, with the Quantum Approximate Optimisation Algorithm and Quantum Annealing as key algorithmic approaches. The paper provides an overview of quantum approaches to routing, logistic network design, fleet maintenance, cargo loading, prediction, and scheduling problems. Notably, most solutions in the literature are hybrid, combining quantum and classical computing. The conclusion highlights the early stage of quantum computing, emphasising its potential impact on logistics and supply chain optimisation. In the final overview, the literature is categorised, identifying quantum annealing dominance and a need for more research in prediction and machine learning is highlighted. The consensus is that quantum computing has great potential but faces current hardware limitations, necessitating further advancements for practical implementation.

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Cited by 4 Pith papers

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