Quantum Computing in Logistics: Revolutionizing Complex Supply Chain Optimization

Around a quarter of delivery trucks in Europe run half-empty. That’s thousands of vehicles burning fuel, clocking driver hours, and adding CO₂ to the air , simply because current computer systems can’t solve complex routing and loading problems fast enough.

This is where quantum computing steps in. It’s not science fiction anymore. Companies like Volkswagen, DHL, Save-On-Foods, BMW, and Airbus are already experimenting with quantum tools to make their supply chains faster, cheaper, and cleaner. The results aren’t perfect yet, but they’re real — and they’re worth looking at.

Smarter Routing: How Volkswagen and DHL Tested Quantum

One of the hardest problems in logistics is routing. A single delivery run can have thousands of possible variations when you factor in traffic, delivery windows, and vehicle limits. Traditional algorithms are good, but they hit a ceiling when things get too complex.

Volkswagen tested this problem in Lisbon during the Web Summit. The company equipped a fleet of buses with routes calculated using a quantum hybrid solver. Instead of relying on static schedules, the system took in live traffic and passenger data. The result? Shorter travel times, less congestion, and buses arriving when they were supposed to. It showed that quantum tools could handle the messiness of real city traffic better than static planning.

DHL has run similar pilots in congested cities. Their experiments suggested that quantum-driven routing could reduce driven miles by up to 10%. That’s a big deal. For a delivery network covering millions of miles per year, 10% less fuel burned is both a cost saving and an emissions win.

The takeaway here is simple: routing is no longer just about getting from A to B. It’s about cutting waste at scale, and quantum gives companies new ways to do that.

Loading More into the Same Space: BMW, Airbus, and Parcel Carriers

Another pain point in logistics is vehicle and container loading. Anyone who’s worked in distribution knows that a poorly packed truck wastes space. A truck that’s 80% full is really 20% inefficient.

BMW used quantum computing to look at how parts are sequenced and packed in its assembly plants. The challenge wasn’t just “fit everything inside”  it was “fit it in the right order so workers can access parts when needed.” Quantum models helped BMW explore more possible packing sequences than classical computers could manage. The result was smoother workflows and less wasted time on the factory floor.

Airbus faced a different challenge: cargo loading in planes. Safety, weight distribution, and turnaround time all compete. Using quantum optimisation, Airbus tested ways to cut down delays while still respecting every safety rule. Faster loading means planes can spend more time in the air, where they make money, instead of sitting at the gate.

In parcel delivery, the problem looks simpler but adds up quickly. A European parcel carrier tested quantum-assisted loading and discovered they could fit 7–8% more parcels into each truck. That may sound small, but across a fleet it allowed them to take one entire truck off the road every day. That’s fuel, labour, and maintenance costs avoided and fewer emissions.

Loading isn’t glamorous, but it’s one of the most expensive parts of logistics. If quantum can squeeze even a few extra percentage points of utilisation, the payback is huge.

Keeping Things Flowing: Sequencing and Slotting in Factories

In manufacturing and warehousing, sequencing is a constant headache. You can’t just throw tasks, parts, or shipments in any order. Safety rules, capacity limits, and timing constraints all compete. When traditional systems clash, you get bottlenecks.

BMW and Airbus both tested quantum models for sequencing problems. For BMW, it meant sequencing parts in production without creating clashes. For Airbus, it meant planning maintenance and inspection tasks in a way that avoided downtime. In both cases, quantum tools gave planners more flexibility. They didn’t just solve problems faster, they found schedules that were more resilient to unexpected changes.

The point here is that sequencing isn’t about speed alone. It’s about keeping operations steady even when the unexpected happens.

Also Read: Revolutionising Supply Chains: Smart Contracts for Automated Shipment Verification with Blockchain Technology

Fairer and Faster Rostering: The Save-On-Foods Example

Scheduling people is just as complex as scheduling machines. A Canadian supermarket chain, Save-On-Foods, had a rostering problem. Creating fair staff schedules used to take 25 hours of manual work each week. Managers had to balance shifts, fairness, labour laws, and demand spikes. It was exhausting and error-prone.

With the help of D-Wave’s quantum hybrid solver, the company automated the process. Rostering time fell from 25 hours to less than 2 minutes. Even more importantly, the schedules were fairer and reduced overtime. That meant lower costs for the business and less stress for employees.

This case shows that quantum isn’t just about machines and trucks. It can directly improve how people work ,freeing managers from paperwork and giving staff fairer treatment.

Key Drivers on Which the Pilot Depends

When logistics teams run a quantum pilot, success is measured in hard numbers that map directly to cost, time, and customer experience. 

Five key areas usually stand out:

1. Fuel and Miles Saved

Fuel is one of the biggest costs in logistics. Even a 5% cut in miles translates into huge savings when scaled across thousands of daily deliveries.

• Volkswagen in Lisbon tested a quantum routing system on buses. By factoring live passenger demand and traffic, they reduced congestion and shortened routes — showing real potential for 5–10% fuel savings.
• DHL couriers ran pilots with D-Wave to optimise courier routes. Results showed similar 5–10% efficiency gains, reducing miles driven and CO₂ emissions.

2. Planning Time

Logistics planning often eats up managers’ hours. Quantum-enabled optimisation can collapse this timeline dramatically.

• Save-On-Foods, a Canadian grocery chain, used a hybrid quantum system for employee scheduling. Rostering dropped from 25 hours to just 2 minutes — a 750x speed-up. Managers could finally spend time on higher-value work instead of spreadsheets.

3. Load Utilisation

Every empty space in a truck is wasted money. Quantum-assisted models help fit more parcels into the same fleet.

• A European parcel carrier ran a pilot where hybrid solvers increased truck load factors by 7–8%. That meant one fewer truck was needed on the road each day — cutting labour, fuel, and maintenance costs.

4. On-Time Delivery (OTIF)

Quantum isn’t just about speed , it’s about predictability.

• Airbus, in partnership with BMW, used quantum optimisation for assembly line scheduling. By reducing sequencing conflicts, they improved on-time-in-full (OTIF) rates, making deliveries and production steps more predictable and less prone to delay.

5. Resilience Under Stress

Supply chains break under pressure , storms, strikes, or sudden demand spikes. Quantum’s strength is in testing multiple scenarios quickly, which makes plans more stable.

• Volkswagen’s Lisbon project showed that quantum routing remained more stable during traffic disruptions.
• Food distributors found that quantum scheduling prevented overtime spikes during seasonal peaks, unlike classical heuristics that collapsed.

Also Read: Digital Tools and Strategies for Navigating Supply Chain Disruptions in Project Management

Final Thought

Quantum pilots aren’t moonshot projects. Most cloud-based tests cost under £50,000, which is less than a quarter of what many retailers spend on overtime in a single quarter.

They also don’t carry much risk. Pilots run in parallel with existing systems, so if the quantum approach fails, operations continue as usual.

The reality is that quantum is ready today for specific problems, routing, loading, and rostering. It’s not yet ready for full global supply chain optimisation. But for focused pain points, it’s already paying back.

Quantum computing still feels futuristic, but in logistics it’s already producing practical results. Volkswagen’s smoother bus routes, Save-On-Foods’ faster rostering, BMW and Airbus’s sequencing pilots, and parcel carriers’ fuller trucks all prove the same point: small, targeted quantum projects can deliver measurable savings in just weeks.

The trick is to start small. Pick one bottleneck, run a pilot, measure the numbers, and scale what works. That’s how quantum shifts from being a buzzword to being a real bottom-line advantage.

References:

• https://www.volkswagen-group.com/en/press-releases/volkswagen-optimizes-traffic-flow-with-quantum-computers-16995
• https://arxiv.org/abs/2006.14162
• https://www.dwavequantum.com/resources/application/save-on-foods-quantum-computing-in-grocery/
• https://www.mytotalretail.com/article/the-little-known-secret-to-retail-resiliency-quantum-computing/
• https://www.airbus.com/en/newsroom/press-releases/2023-12-airbus-and-bmw-group-launch-quantum-computing-competition-to-0
• https://aws.amazon.com/blogs/quantum-computing/exploring-industrial-use-cases-in-the-airbus-bmw-group-quantum-computing-challenge/
• https://q-ctrl.com/blog/exploring-the-future-of-quantum-powered-logistics-with-airbus-and-bmw-group
• https://www.press.bmwgroup.com/global/article/detail/T0446782EN/bmw-group-and-airbus-reveal-winners-of-quantum-computing-challenge?language=en
• https://arxiv.org/abs/2402.17520