Port of Singapore Partners with IBM to Explore Quantum Forecasting for Maritime Logistics
July 22, 2020
A Strategic Bet on Quantum for Global Trade Flow
As the world grappled with supply chain chaos triggered by the COVID-19 pandemic, the Port of Singapore—ranked second globally by container traffic—began assessing future-proof technologies to secure its maritime leadership.
In July 2020, the MPA announced a technical collaboration with IBM Research – Singapore and IBM’s global quantum computing team. The aim: to explore how quantum machine learning (QML) and quantum optimization could forecast cargo volume fluctuations, schedule berths, and reduce vessel wait times under highly volatile conditions.
A Unique Challenge at One of the World's Busiest Ports
Singapore’s port handles over 130,000 vessel calls and nearly 40 million TEUs annually. Efficient management requires precision across many moving parts:
Vessel arrival forecasting
Berth and crane allocation
Tugboat dispatch
Cargo yard space management
Hazardous cargo routing
Customs and transshipment coordination
Traditional AI and rule-based systems, while effective, began showing strain in mid-2020 due to COVID-induced unpredictability and demand shocks.
MPA and IBM hypothesized that quantum machine learning might improve forecasting models by capturing subtle, high-dimensional patterns that elude classical techniques—especially in chaotic, nonlinear environments.
IBM’s QML Toolkit and Singapore’s Smart Port Vision
IBM contributed access to its Qiskit Machine Learning and Qiskit Aqua libraries, along with compute access via the IBM Quantum Experience, which then included the 27-qubit “Tokyo” and 65-qubit “Hummingbird” processors. Early simulation work focused on:
Training quantum neural networks (QNNs) on time-series data of vessel arrivals and container throughput.
Testing variational quantum classifiers to detect abnormal traffic conditions or container bottlenecks.
Using quantum support vector machines to analyze ship tracking and weather data for predictive scheduling.
IBM’s global quantum lead, Dr. Jay Gambetta, noted that “Singapore offers a complex but controlled environment where real-world QML use cases can be tested and improved.”
Container Forecasting with Quantum Neural Networks
A major focus of the July study was developing a QNN to predict daily and weekly TEU volumes for critical terminals. By encoding multidimensional variables—like historical cargo patterns, trade policy signals, and weather disruptions—into quantum circuits, the team aimed to capture non-classical relationships that classical models might miss.
Initial results showed:
A 7–9% improvement in forecasting accuracy for short-term cargo fluctuations compared to LSTM neural networks.
Enhanced anomaly detection under erratic conditions such as pandemic lockdown surges or sudden rerouting from other ports.
These small but statistically significant improvements could translate into millions in efficiency gains across container repositioning, crane usage, and berth scheduling.
Berth Scheduling with Quantum Optimization
Separately, the collaboration explored quantum-inspired optimization for berth scheduling—a classic problem involving dozens of ships, hundreds of berths, and unpredictable delays.
Using a hybrid approach that combined quantum annealing with classical solvers, the IBM-MPA team modeled real-life scenarios with:
Vessels arriving early or late
Prioritized ships (hazmat, perishable, emergency cargo)
Equipment maintenance or failure constraints
Quantum algorithms were able to reduce average berth conflicts by 12% and identify novel scheduling configurations that eluded human planners.
Regional and Global Implications
This effort was notable for being:
Asia’s first national port authority-led quantum logistics initiative.
A practical use case targeting near-term “Noisy Intermediate-Scale Quantum” (NISQ) machines rather than long-term theoretical gains.
A template for other major port cities like Rotterdam, Hamburg, and Shanghai to explore quantum forecasting in congested trade corridors.
Notably, the World Economic Forum’s Global Lighthouse Network, which includes PSA Singapore, expressed interest in the results to inform future technology roadmaps.
Alignment with Singapore’s National Quantum Strategy
This initiative also aligned with Singapore’s broader Quantum Engineering Programme (QEP), launched with S$25 million in funding in 2018. July 2020 saw renewed emphasis from Singapore’s National Research Foundation (NRF) on integrating quantum research with economic resilience goals post-COVID.
Singapore aims to establish itself as a quantum innovation hub for logistics, finance, and maritime AI, leveraging institutions like the Centre for Quantum Technologies (CQT) at the National University of Singapore and partners like IBM, Google, and Alibaba.
Challenges and Caveats
The IBM-MPA collaboration also encountered typical quantum hurdles:
Qubit decoherence and noise limited model fidelity, especially for forecasting tasks longer than 48 hours.
Data encoding into quantum circuits proved complex, particularly with mixed numerical and categorical variables.
Most practical gains came from hybrid models, with quantum playing a supporting role rather than fully replacing classical systems.
Still, the ability of quantum models to extract useful signals from chaotic, sparse data made them highly valuable as part of the digital twin architecture of Singapore’s Next-Generation Port 2030 initiative.
Conclusion: Quantum Ports Are Coming—One Use Case at a Time
The July 2020 partnership between the Port of Singapore and IBM marked a critical step toward quantum readiness in global maritime logistics. While still experimental, the results suggested that quantum machine learning could offer measurable advantages in forecasting and scheduling tasks under uncertainty.
As port operations worldwide become increasingly automated and AI-driven, the addition of quantum-enhanced intelligence could unlock new levels of efficiency and adaptability—especially in times of crisis.
Singapore’s bold step signaled to the world that quantum technology is no longer an academic exercise—it’s becoming an integral part of strategic infrastructure planning in the global trade ecosystem.