Systems science

IHPC utilises advanced computational analytics, modelling, simulation and optimisation to study and understand the dynamics and/or behavior of a broad spectrum of systems. Our researchers harness data & knowledge-driven approaches to uncover deep insight into the nature of these systems and networks.

Key focus areas of interest include urban systems such as transportation, logistics and supply chain, maritime and port operations as well as healthcare. Leveraging on our state of the art expertise, we strive to improve planning processes, operational efficiency and safety, and develop novel solutions for that will bring about positive impact to both public sector agencies and private companies alike.

IHPC aims to model the dynamics and predict emergent behaviour of highly interacting systems through data-driven complexity science.

The core research foci of the group lie in modelling large scale-systems using three broad methodologies:

Using network analysis to understand the dynamics and functional efficiency from the structural connectivity of large-scale systems,
Using agent-based simulations to model dynamic and evolutionary prediction of complex macroscopic behavior of systems, and
To generate useful solutions through scenario-based testing and multi-objective global optimisation

We have already developed various end-user applications in the Transport & Urban Mobility industry and is targeting to replicate this success in the Urban Planning and Energy domains.

Transport agent-base simulation

IHPC aims to support the transition to sustainable energy through modelling, simulation, and optimisation of integrated multi-energy systems. We seek to develop methodologies and tools to effectively incorporate emerging energy resources and improve the efficiency and resilience of future sustainable energy systems.

Capabilities that are being developed in this area include:

Power flow analysis and optimisation and applying these to operation problems such as peak load management, volt-var optimisation, and feeder reconfiguration
Modelling and optimisation of renewable and distributed energy resources such as electric vehicles, solar photovoltaic, and energy storage systems (i.e., smart charging, energy storage scheduling)
Application of power flow and energy resource models to infrastructure planning and policy analysis problems such as network configuration, resilience assessment, and optimal resource siting

IHPC has developed solutions in Maritime and Port traffic safety, Logistics and Supply Chain Management, Risk Management, and Safety and Reliability of industrial systems, simulating and optimising system operations with predictive as well as operational analytics based on big data.

We are currently working on improving the operational efficiency of port operation as well as Collision Risk Detection and proactive management for maritime traffic safety. This can be accomplished by using big data analytics, the usage of predictive models as well as application of AI-based simulation and optimization in multiscale levels.

Moving forward, IHPC aims for increased collaboration with institutes of higher learning (IHL), small to mid-sized enterprises (SMEs), law enforcement (LE) and multinational corporations (MNCs) in the areas of Maritime AI, HPC-based analysis, knowledge and big data driven simulation and optimisation technology.

Operations flowchart for tanker shipping

Operations flowchart for tanker shipping at Singapore Port

HPC-enabled vessel voyage event detection

Dengue risk modelling

Systems science

Complex Systems

Energy Systems

Multiscale Optimisation

Systems science

Complex Systems

Energy Systems

Multiscale Optimisation

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