Quantum Leap at Sea: Mitsui O.S.K. Lines and D-Wave Pilot Quantum Optimization for Port Crane Scheduling
February 25, 2022
Tackling Port Congestion with Quantum-Inspired Innovation
The COVID-19 pandemic created unprecedented strains on global supply chains, particularly in Asia-Pacific, where terminal congestion surged to record-breaking levels. Even as vessel schedules normalized, ports continued to face intense pressure to turn ships around faster while handling higher container volumes. One of the most persistent bottlenecks lies in the assignment of quay cranes—the massive machines responsible for loading and unloading containers from vessels.
Quay crane scheduling is deceptively complex. Each crane has specific reach and movement limits, safety zones, and maintenance schedules. Ships vary in length, cargo type, and handling priority. Traditional scheduling relies on heuristic algorithms and operator expertise, but these approaches struggle with real-time disruptions such as late vessel arrivals or unexpected equipment downtime.
Recognizing the limitations of conventional methods, Japanese shipping giant Mitsui O.S.K. Lines (MOL) turned to quantum computing. Partnering with Canadian quantum pioneer D-Wave Systems, MOL initiated a pilot program in Southeast Asia to test whether quantum annealing could deliver measurable efficiency gains in port crane scheduling.
Quantum Annealing for Crane Assignment Optimization
At the heart of the project was D-Wave’s Advantage quantum system, a platform built for combinatorial optimization problems. Unlike gate-based quantum computers, which are still largely experimental, D-Wave’s quantum annealers are commercially available and designed to work on problems expressed as Quadratic Unconstrained Binary Optimization (QUBO).
The MOL pilot formulated crane scheduling as a QUBO problem. Constraints such as crane reach, movement conflicts, ship size, and maintenance windows were encoded into quantum-ready structures. Priority cargo, including refrigerated containers and time-sensitive goods, received weighted optimization values.
The hybrid solver approach—combining classical pre-processing with quantum annealing—was tested across scenarios involving 5 to 20 ships and up to 50 cranes. The goal was to simulate realistic peak conditions in high-traffic ports, where scheduling complexity is most severe. Results were benchmarked against traditional scheduling software currently used in MOL terminals.
Pilot Results and Measurable Gains
The pilot, carried out at a partner terminal in Southeast Asia (kept undisclosed due to commercial agreements), delivered tangible operational improvements:
12% reduction in vessel berth time, directly cutting down costly delays.
18% improvement in crane utilization, meaning less idle machinery and more efficient task allocation.
Fewer crane conflicts in overlapping movement zones, reducing downtime caused by safety holds.
Greater predictability in container discharge and loading, improving downstream truck and rail scheduling.
These measurable gains provided evidence that quantum-enhanced optimization could move beyond theory into real-world maritime logistics. MOL and D-Wave co-published a technical brief and prepared to present findings at the 2022 International Conference on Ports and Shipping Innovation, highlighting the global relevance of the pilot.
Strategic Context for MOL
For MOL, the pilot was not an isolated experiment but part of its larger "Ishin Next" Digital Transformation Program, which aims to build a smarter, greener, and more resilient logistics ecosystem. Key initiatives under this program include:
Smart port infrastructure, integrating AI, IoT, and blockchain into daily operations.
Fleet optimization, using advanced analytics to minimize emissions and fuel costs.
Data-driven decision support, creating real-time visibility across terminal operations.
MOL’s quantum pilot also fits into Japan’s broader innovation push. Supported by the Moonshot R&D program and METI’s incentives for logistics modernization, Japan has emphasized industrial applications of quantum technologies. MOL’s partnership with D-Wave provided a concrete example of this policy vision in action.
Alongside quantum efforts, MOL has active collaborations with NEC on maritime AI systems, IBM Japan on digital twins for vessel routing, and the Port of Yokohama on 5G-enabled automation trials. By layering quantum optimization into this portfolio, MOL positioned itself at the forefront of next-generation logistics.
D-Wave’s Port Logistics Use Case Expansion
For D-Wave, the collaboration with MOL marked an important milestone. The company had previously demonstrated applications in retail supply chain optimization, airline crew scheduling, and vehicle routing in smart cities. Extending into port logistics validated the versatility of quantum annealing for constrained resource allocation problems.
Alan Baratz, CEO of D-Wave, emphasized that maritime logistics presents a “perfect case study” for quantum annealing. Ports involve multiple constraints, dynamic inputs, and enormous solution spaces—conditions where classical heuristics falter but quantum annealing thrives. Unlike gate-model quantum computing projects, which remain experimental, D-Wave’s hybrid systems provided immediate, measurable results.
Industry and Regional Implications
The MOL-D-Wave partnership is emblematic of a wider regional trend. In Southeast Asia and Northeast Asia, ports and governments are investing in quantum-inspired logistics innovation:
Singapore: PSA International partnered with the Singapore Maritime Institute to investigate AI and quantum optimization for mega-terminal operations.
Thailand: The Eastern Economic Corridor (EEC) launched digital port testbeds exploring quantum-enhanced planning.
South Korea: The Port of Busan began simulation pilots with KAIST to study quantum scheduling scenarios.
Japan’s National Strategy for Quantum Technology (2020) explicitly called for industrial-scale deployment. MOL’s pilot delivered a tangible example of how quantum computing can be deployed to solve long-standing challenges in port operations.
Technical Considerations and Challenges
Despite strong results, MOL and D-Wave acknowledged several challenges before scaling:
System integration: Bridging terminal operating systems (TOS) with quantum solver modules required new data pipelines.
Runtime performance: Ensuring solver results fit within tight operational cycles was critical.
Change management: Port operators required training to interpret and trust quantum-generated schedules.
To mitigate these issues, MOL embedded quantum analysts directly into terminal planning teams and conducted joint scenario workshops. This hands-on approach smoothed the learning curve and built operational confidence.
The Road Ahead: From Pilot to Production
Looking forward, MOL outlined an ambitious roadmap:
Scaling deployments: Extend quantum optimization to terminals in Japan and Vietnam.
Expanding scope: Incorporate container yard optimization and gate-out scheduling into the solver framework.
Forming alliances: Launch a port innovation consortium with technology vendors, government agencies, and logistics stakeholders.
The long-term vision is an end-to-end quantum optimization layer that spans vessel berthing, crane allocation, yard management, and intermodal dispatch.
Conclusion: Quantum Enters Maritime Mainstream
The MOL-D-Wave pilot, launched on February 25, 2022, represents one of the most advanced demonstrations of quantum optimization in global maritime logistics. The results showed not only efficiency gains but also a pathway for integrating quantum into daily port operations.
As the shipping industry faces mounting pressure to digitize, decarbonize, and streamline, quantum computing offers an invaluable new toolkit. MOL’s initiative highlights that quantum innovation is no longer a distant frontier but an emerging operational reality.
If scaled successfully, MOL may set the precedent for quantum-powered ports across the Asia-Pacific and beyond, where efficiency and resilience are key to sustaining global trade.