Singapore’s PSA International Partners with IBM Quantum to Explore Port Flow Optimization
October 28, 2021
Singapore as a Quantum Logistics Testbed
Singapore’s port is one of the busiest and most technologically advanced in the world. As global supply chains were reeling from pandemic-related congestion in 2021, PSA International sought new computational tools to address rising throughput complexity, variability, and real-time disruption.
Recognizing the combinatorial nature of port operations—especially in berth allocation and container shuffling—PSA partnered with IBM Quantum to evaluate whether quantum-enhanced solvers could offer breakthroughs beyond classical optimization methods.
This made PSA one of the first major port operators to publicly pursue quantum computing as a long-term solution to logistics challenges.
Project Goals: Managing Uncertainty at the Quay
The PSA–IBM collaboration focused on three core problems:
Berth allocation optimization under unpredictable vessel arrival times.
Container yard reshuffling to reduce re-handling costs and crane idling.
Disruption recovery strategies after delays, equipment failure, or bad weather.
The goal was to improve performance in scenarios with millions of variables, limited planning windows, and real-time data constraints. These are precisely the kinds of problems quantum computers—especially hybrid systems—are expected to address in the coming decade.
IBM Quantum Systems in Use
The pilot utilized IBM’s gate-based quantum computing systems available through the IBM Quantum Network, particularly its:
27-qubit Falcon processors for early-stage modeling.
Qiskit SDK for algorithm development.
Cloud-based access via the IBM Quantum Experience platform.
The team experimented with quantum-inspired and quantum-native algorithms, depending on problem size and solver maturity.
Use Case 1: Quantum-Aware Berth Scheduling
Berth scheduling involves aligning ship arrivals with limited dock space, accounting for:
Arrival time uncertainty
Ship size and crane requirements
Loading/unloading durations
Tidal and weather influences
The team developed a quantum-enhanced constraint satisfaction model that mapped these variables to a qubit register.
Using Variational Quantum Eigensolver (VQE) techniques and hybrid preprocessing, IBM’s solvers explored berth-slot permutations that minimized vessel waiting time while balancing crane utilization.
Initial simulations on IBM’s 27-qubit system demonstrated:
Higher solution diversity for last-minute vessel bunching
Smoother allocation outcomes under arrival-time variability
A 6–9% reduction in average berth waiting times in small-scale trials
Use Case 2: Container Yard Optimization
In large ports like Singapore’s Tuas or Pasir Panjang terminals, containers are stacked in dense yards where reshuffling is costly and time-consuming.
PSA tested Quantum Approximate Optimization Algorithm (QAOA) formulations to:
Minimize rehandling during container retrieval
Predict optimal yard stacking layouts based on ship schedules
Improve yard crane task assignments
The quantum solver outperformed classical heuristics in some constrained layouts, particularly when:
Delivery windows were tight
Stacks had uneven height constraints
Yard zones had varied reachability
Though the quantum system could only simulate limited container sets, the findings highlighted how quantum heuristics may enhance layout planning, especially as hardware scales.
Use Case 3: Reactive Scheduling After Disruptions
Ports frequently face unexpected delays—e.g., from crane failures or customs issues. PSA and IBM modeled how quantum systems might aid disruption response by rapidly reassigning berths and crane jobs.
The goal was to reduce total downtime across the yard by recalculating all impacted resource allocations within seconds.
The hybrid quantum-classical pipeline used:
Real-time disruption inputs
A decision tree encoded into a quantum circuit
Classical post-processing for feasibility validation
Though still in early phases, the approach showed potential in reducing cascading delays—by generating faster, more balanced recovery plans than existing rule-based systems.
Strategic Objectives and Ecosystem Fit
The PSA–IBM project aligned with several broader strategic objectives:
Operational resilience: Building tools for rapid decision-making under uncertainty.
Digital leadership: Reinforcing Singapore’s status as a smart port innovation leader.
Quantum capacity-building: Training logistics engineers in quantum modeling techniques.
Singapore’s national initiatives such as the Quantum Engineering Programme (QEP) and Port 4.0 Transformation Roadmap actively supported such experiments as part of a long-term digital trade strategy.
Global Context: Quantum Port Logistics Takes Shape
The PSA–IBM announcement marked a significant point in the emergence of quantum logistics in port operations. Globally:
Port of Los Angeles began collaborating with USC on quantum scheduling models.
Rotterdam’s Digital Twin Program explored quantum algorithms for container flow forecasting.
Hamburg Port Authority initiated quantum research with DLR and Siemens in late 2021.
Together, these initiatives signaled the formation of a quantum-ready port ecosystem, where early experimentation is laying the groundwork for the 2030s.
Challenges Identified
While promising, PSA and IBM acknowledged several current limitations:
Quantum volume was too small for full-port-scale problems.
Data integration from IoT, TMS, and ERP systems needed preprocessing pipelines.
Talent readiness: Bridging port operations and quantum programming required new cross-disciplinary roles.
IBM began working with NUS and NTU to develop quantum training modules for supply chain professionals, aiming to close the skills gap over time.
Toward Port Optimization-as-a-Service
IBM’s roadmap included offering port-specific quantum optimization modules via its cloud-based IBM Quantum Services, enabling:
Simulation-based planning for shipping alliances
Real-time decision-support dashboards for quay operators
APIs that port logistics software vendors can integrate with
PSA expressed interest in developing a modular quantum layer within its internal optimization stack—allowing planners to test quantum-generated options alongside classical models.
Environmental and Economic Impacts
The pilot also linked to sustainability metrics:
Improved berth scheduling reduces fuel usage from idling vessels
Better yard layout planning can lower crane energy consumption
Faster disruption response minimizes demurrage and late penalties
Even small gains from quantum planning can have compound environmental benefits across thousands of daily container movements.
Conclusion
The October 2021 collaboration between PSA International and IBM Quantum marked a major step in integrating quantum computing into port logistics. Focused on berth scheduling, yard operations, and disruption management, the pilot demonstrated how early-stage quantum algorithms can complement classical systems in managing uncertainty and complexity.
As hardware scales and hybrid solvers evolve, port operators like PSA are laying the foundations for quantum-enhanced global trade infrastructure, positioning themselves ahead in the digitalization of logistics.