D-Wave Launches Quantum Hybrid Logistics Pilot with Save-On-Foods
October 8, 2020
Quantum Meets Grocery Logistics: A First in North America
Quantum computing has long promised solutions to complex logistical challenges, from vehicle routing to supply chain optimization. In October 2020, this potential took a leap toward reality as D-Wave Systems, a Canadian pioneer in quantum annealing, announced a collaboration with Save-On-Foods — one of Western Canada’s largest grocery chains — to optimize its delivery routes using hybrid quantum computing.
As online grocery demand surged due to COVID-19, logistics networks faced unprecedented stress. Save-On-Foods, operating more than 170 locations, needed smarter ways to adapt its routing and delivery systems. Through this collaboration, D-Wave’s hybrid solver service (HSS) and quantum annealing platform were deployed to reduce delivery times and costs across select urban and suburban delivery zones.
This marked a critical milestone: while quantum computing has mostly remained within academia or defense sectors, this pilot brought it directly into the world of commercial last-mile logistics.
Why Hybrid Quantum for Grocery Logistics?
The vehicle routing problem (VRP) is a classic NP-hard challenge: determining the most efficient set of routes for a fleet of delivery trucks, given constraints like customer locations, time windows, and delivery capacities. While classical algorithms can solve small-scale VRPs, performance degrades exponentially with complexity — especially when considering thousands of stops and dynamic conditions like weather, traffic, and time-based demand surges.
Quantum annealing, D-Wave’s specialty, offers an alternative by efficiently exploring combinatorial solution spaces. D-Wave’s hybrid solver service combines classical optimization algorithms with quantum subroutines that solve discrete chunks of the problem — ideal for routing, slotting, and scheduling.
In Save-On-Foods' case, the challenge was adapting delivery zones and routes to minimize fuel usage while meeting customer expectations in densely populated areas like Vancouver and its surrounding suburbs.
Technical Approach
The Hybrid Quantum Platform
The HSS works by accepting a Quadratic Unconstrained Binary Optimization (QUBO) model — a mathematical representation of the routing problem. The model incorporates delivery constraints, warehouse stock levels, traffic density forecasts, and vehicle limitations.
The classical layer first breaks down large problems into smaller subproblems, then hands these subproblems to the quantum annealer. The annealer returns possible solutions, which are evaluated and combined into a final route configuration.
This quantum-classical feedback loop allows for rapid iteration and dynamic adaptation, something traditional solvers struggle to do in real-time with fluctuating input variables.
Pilot Scope
The trial covered approximately 40 delivery zones across British Columbia, with each zone receiving daily quantum-optimized route plans. Key performance indicators (KPIs) measured during the pilot included:
Reduction in total delivery miles
On-time delivery rate improvement
Computational runtime versus traditional solvers
Fuel consumption changes
Early Results and Insights
Though full data from the pilot remained under NDA at the time, executives from both D-Wave and Save-On-Foods shared preliminary insights during a public webinar hosted by the Vancouver Quantum Tech Hub on October 28, 2020.
Key reported outcomes included:
12–15% reduction in total mileage across pilot zones
9% improvement in on-time delivery metrics
Sub-second solution time for subproblems (compared to ~90 seconds on classical route optimizers)
Ability to simulate up to 3,000 delivery scenarios per day — enabling fast contingency planning during peak hours
These early results positioned hybrid quantum approaches as viable contenders in real-world logistics applications, especially when traditional infrastructure reached scaling limits.
A Quantum Supply Chain in the Making
The Save-On-Foods trial is part of a broader trend in 2020: logistics companies around the world began looking seriously at quantum-powered decision support tools.
In Japan, Mitsubishi Chemical and Groovenauts launched a separate project using quantum annealing to improve chemical product shipping schedules. In Germany, Volkswagen had begun piloting quantum-enhanced traffic flow optimization in urban centers. But D-Wave’s grocery-focused pilot was among the first to directly impact last-mile logistics for consumers.
It also opened the door to a new conversation: how can quantum optimization become a core layer in logistics management systems (LMS) alongside AI and IoT?
Integration with AI and Demand Forecasting
Another interesting element of the Save-On-Foods partnership was the interplay between AI-based demand forecasting and quantum-based routing. The grocery chain used machine learning models to predict demand surges — especially relevant in COVID-era shopping patterns — and fed those forecasts into the quantum optimizer.
This demand-driven logistics approach ensured delivery fleets were deployed efficiently, reducing idle time and improving service levels.
In future iterations, D-Wave suggested adding even deeper integration, such as quantum-enhanced warehouse picking optimization and real-time reshuffling of delivery priorities based on live conditions.
Strategic Implications for Logistics Firms
The successful trial has significant implications:
Quantum ROI Emerges: One of the biggest criticisms of quantum computing has been lack of real-world ROI. This pilot offered tangible returns — fuel savings, efficiency gains, and improved service metrics — within a short time frame.
Operational Use Cases: It proved that quantum optimization is no longer limited to simulations or research — it can drive actual delivery schedules in fast-paced retail environments.
Cloud Accessibility: D-Wave’s HSS is cloud-based, which means even mid-sized logistics providers could begin exploring hybrid quantum optimization without on-premise quantum hardware.
Challenges and Considerations
Despite success, the pilot wasn’t without limitations. D-Wave acknowledged several challenges:
Scalability: Routing complexity still requires breaking problems into smaller pieces. The quantum annealer isn’t yet capable of processing entire large-scale networks independently.
Data Preprocessing: High-quality, structured logistics data is a prerequisite. Inconsistent inputs can degrade optimization quality.
Black Box Perception: Some route planners initially resisted trusting the quantum-driven recommendations, requiring training and confidence-building.
To address these, Save-On-Foods and D-Wave are developing visual route comparison dashboards and interpretability tools to make the optimization logic more transparent for operations staff.
Looking Ahead: Expansion and Industry Adoption
Following the October pilot, D-Wave announced plans to expand the solution to other retailers and logistics firms in Canada and the U.S. by mid-2021. Early discussions were underway with freight consolidators and cold-chain delivery providers.
D-Wave also committed to continuing its roadmap toward higher-qubit, more error-resistant quantum systems — with the launch of its next-generation Advantage processor (5,000+ qubits) expected to unlock even more complex logistics optimization possibilities.
For Save-On-Foods, the partnership signaled the beginning of a broader transformation toward quantum-enhanced decision-making across the supply chain — from inventory to delivery.
Conclusion: A Landmark in Quantum Logistics
The October 2020 partnership between D-Wave and Save-On-Foods marked a watershed moment for quantum computing in logistics. By demonstrating measurable benefits in last-mile delivery optimization, the project validated hybrid quantum computing as a powerful, accessible tool for solving real-world supply chain challenges.
As logistics networks globally face increasing complexity — from pandemic disruptions to eCommerce spikes — quantum optimization is emerging as not just a futuristic possibility, but a practical tool for today’s operations. This collaboration serves as a blueprint for how logistics firms can start integrating quantum capabilities incrementally — with high returns and minimal disruption.