Honeywell Quantum Solutions and DHL Explore Quantum-Driven Cargo Optimization

Building Quantum-Aware Supply Chains

DHL has long emphasized digital innovation, from warehouse automation to predictive analytics. In 2021, the logistics giant deepened its future-tech play by piloting quantum computing use cases in collaboration with Honeywell Quantum Solutions. Their joint goal: determine how quantum algorithms could enhance multi-modal cargo efficiency across air, sea, and port logistics.

The initiative was focused on three key areas:

• Cargo slot allocation and loading sequencing

• Cross-modal route optimization

• Real-time disruption mitigation through predictive modeling

This marked a notable shift from theoretical studies to direct application testing using Honeywell’s advanced trapped-ion quantum hardware—at the time among the highest fidelity commercial quantum systems.

The Quantum Hardware at the Core

Honeywell Quantum Solutions’ processor, the H1 trapped-ion quantum computer, served as the backbone of the experiment. Key technical advantages included:

• Mid-circuit measurement, allowing decision branches within computations.

• All-to-all connectivity, improving qubit interaction efficiency.

• High gate fidelity above 99.9%, which allowed more reliable algorithm execution.

DHL’s logistics problems, highly combinatorial in nature, were ideal for early-stage quantum optimization testing—especially for modeling allocation constraints in shipping containers and air cargo pallets.

Use Case 1: Cargo Load Optimization

The first use case modeled a simplified version of DHL's cargo loading workflows:

• Containerized freight had to be packed within dimensional and weight constraints.

• Regulatory and destination rules created additional hard constraints.

• Optimization goals included minimizing empty volume and maximizing delivery timeliness.

Using quantum approximate optimization algorithms (QAOA), the team encoded cargo combinations and constraints into qubit states. Early-stage runs on Honeywell's H1 processor showed potential benefits in:

• Reducing computational time for constrained packing problems.

• Enabling flexible load configurations in response to late shipment changes.

While classical solvers remain more scalable today, the quantum approach delivered novel solution paths that helped DHL rethink its heuristic models.

Use Case 2: Air-Sea Intermodal Coordination

The second use case addressed route optimization across multimodal journeys—e.g., moving cargo from air hubs to sea ports with tight handoff windows.

DHL modeled a regional network involving:

• European cargo flights arriving at major airports (e.g., Frankfurt, Heathrow).

• Cargo transfers to sea-bound shipments via truck corridors.

• Port departure timelines and loading capacities.

The problem was mapped onto a quantum-inspired graph traversal model with resource constraints (vehicle capacity, distance, time windows).

Running hybrid solvers—combining Honeywell’s quantum processor with classical optimization layers—the system tested several intermodal handoff scenarios. Results demonstrated:

• Better adherence to tight deadlines.

• Reduced late departures due to smarter truck-port alignment.

• A foundation for co-optimizing freight timing across transportation modes.

Use Case 3: Disruption Simulation and Response

In a third experiment, DHL simulated a cargo disruption scenario (e.g., a missed connection at an intermediate hub). Quantum-enhanced solvers were used to:

• Reconfigure cargo plans within seconds of the disruption.

• Explore thousands of alternative configurations for re-routing.

• Prioritize critical cargo items based on urgency and perishability.

While current quantum machines are not fast enough for live, global-scale replanning, the prototype showed that quantum techniques can rapidly suggest high-quality alternatives in complex, high-constraint systems—potentially acting as decision-support modules.

Strategic Rationale and Long-Term Vision

DHL Supply Chain emphasized that while near-term quantum supremacy in logistics is years away, the early involvement helps:

• Build internal quantum literacy among operations planners.

• Test integration methods with existing transport management systems (TMS).

• Develop a library of quantum-friendly logistics use cases.

Honeywell (now part of Quantinuum) saw the partnership as proof that real-world logistics firms are ready to experiment with quantum hardware. The goal is not replacing classical systems outright, but enhancing combinatorial modeling capabilities.

Industry Impact and Quantinuum’s Evolution

Honeywell’s quantum division would soon merge with Cambridge Quantum to form Quantinuum, one of the largest integrated quantum computing firms by late 2021. The DHL pilot became part of Quantinuum’s logistics and supply chain research showcase.

This reflected a broader logistics trend, as companies began formalizing quantum innovation pathways:

• UPS and Zapata Computing launched a quantum route planning initiative.

• FedEx began exploring quantum cryptography for package security.

• DB Schenker partnered with Fraunhofer to study quantum forecasting.

The DHL-Honeywell project stood out as one of the first to test gate-based quantum processors on real-world freight problems, rather than relying solely on emulators or annealing platforms.

Technical Lessons and Constraints

Key takeaways from the October 2021 experiments included:

• QAOA tuning is non-trivial: Performance was highly sensitive to parameter settings.

• Hybrid integration works best: Classical pre-processing helped reduce quantum circuit depth.

• Scalability is still a challenge: Models were limited to small cargo batches and regional networks due to hardware limits.

Still, DHL and Quantinuum agreed that with scaling advances, these methods could handle full-fleet optimizations in future logistics planning.

Toward Quantum-Enhanced Logistics Platforms

Looking forward, DHL planned to:

• Create a quantum sandbox for internal logistics experiments.

• Partner with Quantinuum to build domain-specific applications, including cargo delay risk scoring and slot allocation tools.

• Publish its results in open-access quantum-logistics journals to help shape industry standards.

Quantinuum, meanwhile, began offering its InQuanto and TKET platforms to logistics clients, enabling broader experimentation beyond DHL.

Policy and Market Alignment

This quantum cargo research aligned with EU and global efforts to modernize supply chains:

• The EU’s Digital Compass roadmap promotes quantum and AI investments in transport.

• Germany’s Federal Ministry of Digital and Transport began exploring next-gen routing for air and freight mobility hubs.

• The World Economic Forum identified quantum logistics as a priority use case for sustainable freight networks.

Challenges and Opportunities

Despite promise, several hurdles remained:

• Hardware limitations: Qubits and coherence times still limit complexity.

• Workflow integration: Embedding quantum tools into existing DHL systems required custom interfaces.

• Skill gaps: Both DHL and Quantinuum faced challenges in recruiting quantum-savvy supply chain engineers.

But the upside is clear: quantum modeling may offer new paths to optimization in a sector increasingly pressed by global delays, emissions targets, and cost volatility.

Conclusion

The Honeywell-DHL quantum logistics pilot in October 2021 was a milestone in translating quantum theory into applied cargo operations. By tackling real freight problems with early gate-based processors, the project validated quantum’s long-term potential in global logistics.

Though still in the experimental phase, such pilots help de-risk future deployments and establish quantum-aware planning as part of logistics digitalization. DHL’s leadership may inspire broader adoption across the freight sector—especially as quantum hardware and hybrid software continue to evolve.