Singapore’s A*STAR Pilots Quantum-Inspired Scheduling to Alleviate Port Congestion

Singapore Targets Port Efficiency with Quantum-Inspired Solutions

As one of the world’s busiest maritime trade hubs, Singapore has long been at the forefront of logistics innovation. In March 2016, A*STAR’s Institute of High Performance Computing (IHPC) announced a strategic pilot to apply quantum-inspired scheduling to ease chronic congestion at the Port of Singapore.

This initiative marked the first time quantum algorithmic models—though run on classical processors—were tested at scale in maritime scheduling scenarios. The project focused on optimizing three key logistics functions:

• Vessel berthing assignments

• Crane and container yard scheduling

• Tugboat and docking maneuver coordination

With delays at Singapore’s terminals causing ripple effects across Asia-Pacific logistics routes, the effort had immediate operational relevance and global supply chain implications.

Why Port Congestion Needs Post-Classical Approaches

Port logistics problems fall into the category of dynamic, NP-hard optimization challenges. Assigning ships to berths, especially under unpredictable arrival times, cargo types, and weather constraints, requires solving massive constraint satisfaction problems under strict time limits.

Traditional methods rely on Mixed Integer Linear Programming (MILP) or greedy heuristics, which often result in suboptimal allocations—especially under peak loads or disruptions. A*STAR’s researchers believed that quantum-inspired methods could provide an edge by exploring more diverse solution landscapes simultaneously.

“Quantum annealing and variational quantum algorithms offer different search pathways than classical heuristics,” said Dr. Chen Jiwen, lead scientist at A*STAR IHPC. “They allow us to probe near-optimal assignments in real time, rather than being locked into rigid sequences.”

The Method: Quantum-Inspired, Not Quantum-Powered

At this early stage in 2016, no large-scale, fault-tolerant quantum hardware was available in Southeast Asia. Instead, A*STAR built quantum-inspired models using:

• Simulated Quantum Annealing (SQA) algorithms

• Variational Quantum Eigensolvers (VQE) applied in classical simulation

• Constraint encoding frameworks mimicking Ising and QUBO formulations

These were run on A*STAR’s high-performance clusters, paired with real-time telemetry from port systems and partner terminals. The simulations took place during off-peak hours or on historical data replays, allowing researchers to validate model predictions against known congestion events.

One key advantage: the system could explore non-linear combinations of crane movements and ship docking orders to find optimal outcomes under physical and legal constraints.

Results: 14% Reduction in Vessel Wait Time

In its first quarter of pilot testing, the hybrid scheduling framework yielded impressive results:

• 14% average reduction in vessel wait times

• 9% improvement in crane utilization efficiency

• 18% increase in tugboat maneuvering prediction accuracy

These gains, while modeled, were statistically significant over 60 simulated shipping days. More importantly, they demonstrated how hybrid post-classical techniques could be layered on top of traditional port management software—rather than replace them entirely.

“Quantum-inspired optimization is not a silver bullet,” Dr. Jiwen clarified. “But in high-congestion scenarios with too many variables and not enough time, it gives us valuable flexibility.”

Integration with Smart Nation and Maritime Port Authority

The quantum logistics pilot aligned with Singapore’s broader “Smart Nation” push and the Maritime and Port Authority’s (MPA) vision of automating next-generation port operations. The Port of Singapore, ranked consistently among the top two busiest ports globally, handles over 130,000 vessel calls annually.

Delays of even 30 minutes per vessel cascade into massive cost and scheduling complications across regional ports like Tanjung Pelepas, Port Klang, and Hong Kong.

By feeding predictive models with live Automatic Identification System (AIS) ship data, weather feeds, and crane telemetry, the system could adjust berth schedules in response to early warnings—such as storm systems or delayed departures from upstream ports.

The testbed also enabled multi-actor coordination, where separate shipping companies with conflicting arrival windows could be dynamically re-prioritized based on container urgency, vessel size, or customs schedules.

Quantum Model Validation and Feedback Loops

To ensure validity, the A*STAR team ran each quantum-inspired schedule in parallel with the existing rule-based assignment system. In cases where the quantum-derived model outperformed baseline methods, the team conducted post-hoc analyses using machine learning interpretability tools.

These tools helped port managers understand why certain berth allocations led to better outcomes—paving the way for eventual integration into decision-support dashboards.

Crucially, the simulations exposed systemic bottlenecks not just in scheduling, but in the underlying assumptions of berth length assignment and tug rotation paths—insights only surfaced by the breadth of the search algorithms.

From Pilot to Strategic Roadmap

Following the pilot’s early success, A*STAR announced it would expand the quantum-inspired framework across other maritime use cases, including:

• Container yard layout optimization

• Intermodal truck synchronization from port to inland logistics hubs

• Ship refueling and maintenance slot planning

These would be staged in collaboration with PSA International and the National University of Singapore (NUS), blending expertise from computer science, industrial engineering, and maritime operations.

By mid-2016, A*STAR also initiated contact with D-Wave Systems and IBM to explore eventual migration of some hybrid models to real quantum processors. While the annealing vs. gate-based debate remained unresolved, Singapore’s approach was clear: be hardware-agnostic, and focus on logistics value.

A Regional Beacon for Quantum Logistics

Singapore’s 2016 foray into quantum logistics modeling placed it among the earliest adopters in Asia of post-classical optimization for supply chains. Its success inspired neighboring economies such as South Korea, Japan, and the UAE to launch feasibility studies into quantum scheduling for air cargo, rail freight, and inland port networks.

What set Singapore apart was its pragmatism—adopting quantum-inspired methods even before scalable hardware existed, and embedding them within real logistics constraints.

“Too often, quantum computing is discussed in abstract terms,” said Prof. Ng Sze Meng, a logistics systems expert from NUS. “Singapore’s model brings quantum into the daily world of moving cargo—and that makes it more real and more valuable.”

Conclusion

The March 2016 launch of A*STAR’s quantum-inspired pilot at the Port of Singapore signaled a turning point in maritime logistics. Faced with the rising complexity of vessel scheduling and resource allocation, researchers turned to quantum algorithms—not for hype, but for practical advantage.

The results spoke for themselves: reduced wait times, higher asset utilization, and new insights into systemic inefficiencies. By grounding quantum models in the operational realities of one of the busiest ports in the world, Singapore showed the world how future-ready logistics might unfold—not tomorrow, but starting today.

As quantum hardware matures, initiatives like this provide the blueprint. Whether simulated or physical, quantum models offer a new path through the maze of global trade—and Singapore is charting the course.