// PROJECTS & DEMONSTRATIONS
Research
My research focuses on the design and evaluation of optimisation methods for complex planning and scheduling problems. I am particularly interested in integrating mathematical programming with heuristic and metaheuristic approaches, supported by data engineering, computational experimentation, and solver benchmarking.
Through my research collaboration with NHS Blood and Transplant, I developed multi-objective optimisation frameworks for large-scale blood collection network planning and scheduling. This work integrated mathematical modelling, algorithm development, road-network distance modelling, and large-scale data processing into a browser-based decision-support platform featuring interactive visualisations and scenario analysis.
My work also includes industrial forecasting for coffee beans and FMCG products at TRG International, alongside an independently developed public case study exploring grocery demand patterns, statistical forecasting methods, and model evaluation.
Selected Research Projects
UK Blood Collection Network Optimisation
University of Portsmouth × NHS Blood and Transplant · United Kingdom
Developed an integrated optimisation framework for national blood collection planning, combining strategic facility location and allocation, resource planning, and multi-period scheduling.
The research involves multi-objective mathematical programming, custom solution algorithms, computational benchmarking, and interactive platform visualisations.
Confidentiality note. The original operational data and implementation are not publicly available due to commercial confidentiality. The independent Mobile Grocery case study, developed using synthetic data in Ontario, Canada, demonstrates related optimisation methods through a broader computational and interactive framework.
Mobile Grocery Retail Network Optimisation
Public DemonstrationIndependent case study · Ontario, Canada
A publicly accessible demonstration of network planning and scheduling methods using synthetic data, including road-network modelling, mathematical optimisation, heuristic algorithms, computational experiments, and interactive decision-support visualisations.
Explore case study →Coffee Beans and FMCG Products Demand Forecasting
TRG International · Vietnam
Developed demand forecasting approaches for 20+ coffee bean products and 150+ FMCG products to support procurement planning and inventory management. Analysed historical demand patterns, incorporating trend and seasonality, and compared forecasts against actual demand to inform purchasing and inventory decisions.
Confidentiality note. The original operational data and implementation are not publicly available due to commercial confidentiality. The independent Dunnhumby case study extends the forecasting concepts explored in this work using publicly available data and a broader methodological framework.
Retail Demand Forecasting and Statistical Modelling
Public DemonstrationIndependent case study · Dunnhumby dataset
An independent forecasting case study extending the approaches explored in my earlier industrial work. Using the publicly available Dunnhumby dataset, the demonstration investigates statistical forecasting methods, SKU-specific tuning, rolling-origin evaluation, and demand variability to develop a more systematic framework for forecasting. Inventory replenishment simulation is planned as a further extension.
Explore forecasting project →