Optimisation often brings diversified contexts under one umbrella. Despite the opulence of existing optimisation approaches, integrating proper methods with real-life applications is still a challenging and onerous task.
The Decision Support and Analytics Research Group is working on many such techniques in diversified domains, including creating different decision support systems (DSS) in decision analytics.
Drawing from a range of skillsets and research specialties, the team has explored various technology decision-making approaches by integrating methodologies related to artificial intelligence and evolutionary algorithms, such as swarm intelligence and nature-inspired meta-heuristic approaches, and information systems, for example, influence maximisation. Throughout this process, we have unveiled a unique dimension in the decision-making literature or technology-enabled decision-making literature.
Similarly, our unique skillset has enabled the team to apply digitalisation-focused optimisation techniques to many important engineering and non-engineering domains. For example, in recent years, we have applied our optimisation skills in many problems related to:
- computer science - resource allocation and management for pattern recognition, image processing, internet of things, cyber-physical systems
- electrical and electronic engineering - identification of photovoltaic cells, augmenting inverters, applying optimisation to pulse width modulation and selective harmonic elimination
- system engineering - simulation-optimisation, multi-criteria decision making.
As industries work to become more sustainable, we have expanded our research to incorporate different aspects of sustainability, including the minimisation of carbon footprint, transportation, energy usage and waste.
Drawing from a range of skillsets and research specialties, the team has explored various technology decision-making approaches by integrating methodologies related to artificial intelligence and evolutionary algorithms, such as swarm intelligence and nature-inspired meta-heuristic approaches, and information systems for example, influence maximisation. This research group has five key research priority areas:
- Data-driven Project Portfolio Management
- Digital Transformation Towards Integration
- Sustainable and Resilience Supply Chain and Logistics
- Socio-economic Systems/Complex Systems
- Artificial Intelligence for Decision Making
