The optimisation team carries out fundamental and applied research that addresses grand challenges faced by our society in environmental and societal resilience, future energy systems, logistics, and supply chains. Our mission is to contribute pioneering scientific results in continuous and discrete data-intensive optimisation, decision-making under uncertainty with data being delivered continuously in real-time to the optimisation engine,  simulation, and visualisation, to build innovative optimisation systems needs to tackle increasingly complex applications and find high-quality solutions under time constraints, exploit uncertainty, deal with large data sets, and be integrated in complex runtime environments. The complexity of this new generation of applications places a significant cognitive burden even on expert practitioners and requires hybridisations of major technologies, such as constraint programming, mathematical programming and local search. We support our client organisations to make good decisions in a wide variety of contexts. We aim to be national leaders in the development of platforms for flexible solutions to real-world problems, particularly Vehicle Routing and Supply Chain solutions