Toshiba and ANA Launch Quantum-Inspired Drone Logistics Routing in Japan
May 23, 2022
On May 23, 2022, Toshiba Digital Solutions and All Nippon Airways (ANA) jointly announced the successful deployment of a quantum-inspired logistics optimization platform designed to schedule and route autonomous drones in rural Japan. The initiative represents one of the most tangible applications of advanced computing in logistics to date, solving pressing delivery challenges in regions where traditional infrastructure is expensive, inefficient, or outright inaccessible.
Tackling Japan’s Rural Logistics Challenge
Japan’s logistics sector has long faced an acute challenge in servicing its rural and aging population. With more than 28% of the country’s citizens aged 65 or older, demand for reliable delivery of daily necessities and medical supplies is increasing. Yet in mountainous, coastal, and sparsely populated regions, traditional truck-based delivery is expensive and often delayed by weather or limited infrastructure.
ANA, which has been developing autonomous drone delivery as a core component of its logistics vision, quickly discovered that optimizing drone operations was far from simple. Constraints such as payload limits, battery range, wind conditions, and shifting demand meant that simple heuristic scheduling methods fell short. The airline needed a system capable of managing combinatorial optimization in real time, balancing multiple variables while ensuring reliability.
Rather than wait for commercial-scale quantum computers, ANA partnered with Toshiba to use the Simulated Bifurcation Machine (SBM)—a classical computing platform inspired by quantum dynamics.
Toshiba’s Simulated Bifurcation Approach
The SBM is not a true quantum computer. Instead, it mimics aspects of quantum bifurcation dynamics to solve optimization problems. At its core, the system translates logistics scheduling challenges into Quadratic Unconstrained Binary Optimization (QUBO) problems.
For ANA’s drones, this meant encoding data such as:
Flight paths and distances
Battery recharge or swap schedules
Delivery windows and package weights
Weather inputs and emergency rerouting needs
The SBM then simulated the system’s evolution, quickly converging on low-energy configurations that represented near-optimal solutions.
Unlike gate-based quantum processors or annealers that require cryogenic cooling and highly sensitive qubits, Toshiba’s SBM runs on conventional hardware but is optimized to handle up to 100,000 variables in real-world applications.
Pilot Project in Hiroshima Prefecture
The first test deployment began in Fukuyama City, Hiroshima Prefecture, in early May 2022. ANA operated a fleet of 12 drones across five rural delivery zones, serving primarily elderly residents who required medical deliveries and daily goods.
The system recalculated schedules every 10 minutes, adjusting to new orders, wind speed changes, and battery depletion.
Key results from the three-week pilot included:
13% reduction in total flight time compared to baseline planning
11% improvement in on-time delivery performance
Fewer canceled flights, due to proactive rerouting under weather disruptions
Improved drone utilization efficiency, ensuring balanced workload distribution
For ANA, these numbers carried significant weight. In logistics networks, even single-digit efficiency improvements translate into cost savings, increased coverage, and more reliable service for customers.
Integration Into ANA’s Broader Vision
ANA has announced its ambition to scale drone logistics across rural and disaster-prone regions of Japan by 2025. The roadmap envisions:
Establishing more than 100 drone bases across remote areas
Using real-time SBM optimization to coordinate fleets
Integrating optimization with 5G connectivity, AI-based weather prediction, and smart city infrastructure
The Hiroshima pilot demonstrated that quantum-inspired systems can serve as the operational brain of this vision, enabling drones to adapt dynamically while minimizing human oversight.
Global Context: Quantum-Inspired Optimization on the Rise
Toshiba’s achievement fits within a broader global movement toward quantum-inspired optimization tools. In parallel with ANA’s pilot, other initiatives gained traction in 2022:
Fujitsu’s Digital Annealer was used by Japan Post and Mercedes-Benz for logistics and factory layout planning.
NEC’s vector annealer targeted port container management and congestion reduction.
Microsoft’s Azure Quantum-Inspired Optimization Engine piloted warehouse layout improvements in the United States.
Japan’s aggressive adoption reflects its pressing demographic and geographic logistics challenges, alongside strong public-private partnerships supported by government programs like the Moonshot R&D initiative, which targets fully autonomous logistics systems by 2030.
Technical Deep Dive: SBM in Action
The SBM’s logistics optimization workflow involved several key steps:
Data Encoding – Customer orders, drone capacity, and delivery zones were transformed into binary variables.
QUBO Formulation – Constraints such as battery range, payload, and delivery windows were mapped as penalties in a cost function.
Bifurcation Simulation – The SBM simulated the system’s progression toward stable states, rapidly identifying near-optimal solutions.
Schedule Deployment – Optimal schedules were sent to ANA’s drone control systems for execution.
Continuous Feedback Loop – Every 10 minutes, the system re-optimized based on real-world conditions.
This rapid refresh rate was crucial in adapting to sudden demand surges, weather shifts, or drone malfunctions, ensuring resilient service.
Quantum-Inspired vs Quantum Hardware
Although the SBM borrows concepts from quantum physics, it is fundamentally classical. Advantages include:
Operates on existing server infrastructure
Scales to tens of thousands of variables
Free from quantum decoherence and noise issues
However, limitations remain:
No true quantum speedup
Requires reformulating problems into QUBO form
Dependent on heuristic fine-tuning for accuracy
For logistics operators, though, these trade-offs are worthwhile. What matters most is the ability to generate fast, adaptive, near-optimal solutions—qualities the SBM delivers today.
Broader Implications for Quantum Logistics
The ANA–Toshiba deployment demonstrates that quantum-inspired computing is not just theoretical but operationally viable for logistics today. Lessons from this pilot highlight several industry-wide implications:
Last-mile delivery and drone routing are prime candidates for optimization technology.
Quantum-inspired tools serve as a bridge, preparing companies for a future where full quantum hardware may unlock additional gains.
Public-private collaborations accelerate innovation, ensuring solutions are tested in real-world environments rather than confined to labs.
For Japan, this project strengthens its positioning as a global leader in smart mobility and next-generation logistics, while addressing the immediate needs of rural communities.
Conclusion
The launch of Toshiba and ANA’s quantum-inspired drone logistics routing system in May 2022 underscores the practical value of advanced optimization today. By deploying the Simulated Bifurcation Machine to manage autonomous drone fleets, ANA improved delivery efficiency, resilience, and adaptability in rural Japan—an achievement that demonstrates how cutting-edge computational models can solve deeply human challenges.
As ANA scales this program toward nationwide coverage, and as other global players adopt similar systems, the logistics sector is entering a new phase where quantum-inspired tools complement existing AI and automation strategies. The Hiroshima pilot may be remembered as one of the earliest and clearest proofs that the future of logistics optimization has already begun.