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5 Min Read

Quantum logistics: Answers to 9 pressing questions

December 23, 2024 / Unisys Corporation

Short on time? Read the key takeaways

  • Quantum computing enables real-time optimization of logistics operations, dramatically reducing calculation times for complex routing and loading challenges. 
  • Benefits include increased capacity utilization, reduced fuel costs and faster response to supply chain disruptions. 
  • The technology works synergistically with AI models to handle complex logistics rules while quantum computing generates real-time solutions. 
  • Implementation is becoming accessible through API integration, allowing companies to adopt the technology without massive IT overhauls. 

From optimizing delivery routes to managing warehouse capacity, quantum computing is leveling up logistics operations. But how does it actually work? What benefits are companies seeing? And is it really accessible?

Chris Arrasmith, senior vice president of Enterprise Computing Solutions at Unisys, recently joined Supply Chain Brain’s Editor-in-Chief Bob Bowman on the publication's podcast to discuss how quantum computing is moving beyond theory into practical applications. In case you missed the episode, we break down the key insights from their discussion about the current state and future of quantum computing in logistics operations. 

#1. What makes quantum computing different from traditional computing?

Unlike traditional computers that use binary digits (bits) of 1 or 0, quantum computing uses quantum mechanics to process multiple states simultaneously. This enables much faster processing of complex calculations, particularly for optimization problems common in logistics

#2. How is quantum computing being applied in logistics today?

Companies can use quantum annealing — a specialized form of quantum computing — for near-real-time capacity optimization, container loading, route planning, disruption response and more. Benefits include increased capacity utilization, fuel savings from reduced aircraft idle time and lower operational costs through faster load planning. 

#3. What is quantum annealing, and how does it help logistics?

Quantum annealing is specialized for solving optimization problems, like finding the best possible path or solution in seconds. For logistics, this means optimizing routes, container loading and handling disruptions in near-real-time rather than taking hours or days with traditional computing. 

#4. What's the relationship between AI and quantum computing in logistics? 

They work together synergistically. Pre-trained AI models handle complex data about package sizes, stacking rules and shipping restrictions, while quantum computing processes this information to generate optimal solutions in near-real-time. 

Organizations can create an optimal compute strategy by combining traditional, high-performance and quantum computing. This approach allows organizations to match each task to the best computing method, enabling real-time solutions for any challenge. 

#5. How does quantum computing handle unexpected disruptions in logistics?

When disruptions occur — like weather events or misrouted containers — quantum-enabled logistics systems can quickly recalculate optimal routes and load plans in near-real-time, minimizing delays and costs while maintaining customer delivery expectations. 

#6. What's unique about implementing quantum computing versus traditional IT systems?

Unlike traditional IT rollouts, quantum computing integration can be streamlined through APIs and pre-trained models. Companies can start small, see results quickly and scale up as needed — no massive IT overhaul required.

#7. Will quantum computing replace human workers in logistics? 

No. While it automates many processes, humans remain essential for systems management, exception handling, advanced decision-making and strategic oversight. 

#8. What results are companies seeing from early implementations?

We’ve seen pilot programs report revenue growth from increased capacity utilization and operational cost reductions via improved load planning. 

#9. What's the future outlook for quantum computing in logistics?

As the technology becomes more integrated with AI and machine learning, we can expect faster problem-solving for complex logistics challenges, more resilient supply chains, improved delivery reliability and enhanced hybrid computing solutions. 

Looking ahead 

While quantum computing may seem complex, it's already delivering tangible benefits in logistics operations. The key is understanding where and how to apply this powerful tool alongside existing systems and human expertise. 

Want to learn more about implementing quantum computing solutions for your logistics operations? Visit unisys.com for additional insights or contact us today