Singapore’s PSA and IBM Launch Quantum Pilot to Redesign Terminal Resource Allocation
August 5, 2021
PSA’s Innovation Mandate Meets Quantum Exploration
PSA International operates some of the world’s largest and busiest transshipment hubs, including Singapore’s flagship terminals at Pasir Panjang and the upcoming Tuas Mega Port. With throughput often exceeding 30 million TEUs (Twenty-foot Equivalent Units) annually, operational efficiency is critical.
In August 2021, PSA’s innovation team partnered with IBM’s Quantum division to address a persistent challenge in large-scale port logistics: resource allocation optimization under real-time variability.
The project focuses on terminal operations that involve complex constraints:
Berth window scheduling for vessels with variable arrival times
Crane sequencing to minimize idle time and container reshuffling
Yard block allocation under spatial and temporal constraints
PSA aims to test whether quantum computing can outperform classical heuristics and rule-based algorithms in dynamic operational settings.
Project Structure: From Classical to Quantum Hybridization
The pilot consists of three major modules, each tied to real operational workflows within PSA’s Singapore terminals:
1. Quantum Berth Optimization
The goal: minimize vessel berthing delays and optimize quay crane deployment by solving a combinatorial problem akin to the Job-Shop Scheduling Problem (JSSP). IBM’s team translated this into a QUBO (Quadratic Unconstrained Binary Optimization) model suitable for quantum annealers and simulators.
2. Yard Crane Scheduling
Crane scheduling is highly dynamic, often disrupted by late containers or re-routing. The project used IBM’s Qiskit Optimization module to co-develop a hybrid quantum-classical solver for optimizing container pick-up and drop-off sequences with minimal conflicts.
3. Yard Block Allocation
Quantum-enhanced clustering techniques were tested to evaluate optimal allocation of yard blocks by destination, minimizing reshuffles and re-handling.
Each module ran in simulation mode, fed with real historical data from PSA’s operational logs and IoT-enabled equipment.
Early Results: Promise in Complexity Management
While full deployment was not yet in scope, simulation trials conducted through August 2021 showed promising early indicators:
Up to 15% improvement in berth schedule adherence during peak window overlap scenarios.
Reduced crane idle time by 8%, attributed to better anticipatory allocation using quantum solvers.
Fewer container reshuffles, leading to improved energy efficiency and fewer delays in yard operations.
These outcomes were benchmarked against PSA’s current heuristic and AI-based systems, revealing that quantum approaches added the most value when the system approached saturation or experienced real-time disruptions—a hallmark of mega-terminal operations.
Why PSA Chose IBM for Quantum Trials
IBM was selected due to its hybrid quantum-classical capabilities and access to:
IBM Qiskit: An open-source SDK for quantum programming
IBM Quantum Network: Providing PSA access to cloud-based quantum hardware
Consulting expertise from IBM Research Asia-Pacific, based in Singapore
The partnership also aligned with Singapore’s National Quantum Computing Hub, allowing co-development with local academia such as NUS and A*STAR.
Quantum Computing in Port Logistics: Strategic Implications
PSA’s experiment with IBM is part of a broader trend where large port operators are investigating quantum computing as a next-gen decision support tool.
Key strategic objectives include:
Enhancing resilience under disruption scenarios (e.g., COVID-19, supply chain imbalances)
Minimizing operational emissions by reducing unproductive crane moves and vessel dwell time
Preparing for future integration with AI and 5G-based control systems
Singapore’s Tuas Port, scheduled to be fully operational by the 2030s, is envisioned as a fully autonomous, AI-augmented port—making quantum computing a natural complement to PSA’s innovation roadmap.
Technical Challenges and Forward Path
Despite early gains, the pilot identified several technical bottlenecks:
Scalability: Current quantum simulators can handle small-to-medium problem sizes, but larger QUBO instances require significant decomposition.
Noise and decoherence: Quantum hardware limitations still affect solution quality in real-world cases.
Skill mismatch: Logistics planners and operations teams require quantum literacy to interpret and trust solver outputs.
In response, PSA and IBM plan to:
Develop customized training for port engineers on quantum-enhanced planning tools
Expand the pilot scope to include inter-terminal logistics coordination
Engage with startups working on quantum ML and error mitigation
Global Context: Quantum Ports on the Horizon
PSA’s quantum pilot reflects a growing international movement:
Port of Los Angeles initiated quantum R&D exploration with NASA’s Jet Propulsion Lab (2021)
Hamburg Port Authority assessed quantum cryptography and sensor fusion models with Fraunhofer IKS
Port of Rotterdam integrated QKD and quantum optimization into its digital twin system (September 2021)
These developments indicate a convergence of quantum computing with smart infrastructure, aiming to redefine global port competitiveness.
Conclusion: Quantum Steps Toward Mega-Terminal Optimization
PSA’s August 2021 pilot with IBM signals a meaningful shift in how ports think about future infrastructure. Rather than solely relying on faster AI or bigger datasets, PSA is investing in a fundamentally different computational paradigm.
If further developed, quantum logistics optimization could help PSA and other global hubs navigate the increasingly volatile demands of maritime trade, setting the foundation for autonomous, intelligent, and resilient port systems by the next decade.