Our research engages with the complexities of projects across small and large projects to develop:
- better methods and tools to track project or program success factors
- more effective solutions for managing uncertainties and risks in a complex project or program environments
- more agile and accurate decision-making tools for various phases of projects or programs life cycles
- improved achievement of goals and benefits in project-based organisations
- Combining computational, mathematical, and qualitative approaches to project, program and portfolio management and control.
- Focusing on data-driven project management and scheduling approaches to better integrate business rules and principles along the line of conventional project management.
- Utilising new approaches to incorporate various uncertainties and dynamic behaviours in complex project environments.
- Developing advanced decision-making tools considering various criteria over time with proper implementation of advanced techniques (e.g. evolutionary algorithms, machine learning tools, multi-method approaches) to achieve high-quality results.
- Developing comprehensive dynamic risk assessment models based on risk interdependencies and uncertainties in various project life cycle phases.
- Development of robust project control tools considering multiple uncertainties in resources and overall material supply chain.