This project addresses the critical need to improve decision-making in facility location by explicitly incorporating the value of information into multi-stage processes. Locational decisions often have far-reaching impacts, with long-term consequences and substantial costs tied to suboptimal choices. Despite advancements in handling uncertainty, current approaches rarely account for the dynamic and adaptive nature of information acquisition and its influence on decision-making quality.

The collaboration with Scottish Water offers a unique opportunity to explore sensor placement as a real-world application of this concept. Sensors not only provide valuable data for infrastructure management but can also be relocated, allowing us to model and test dynamic methodologies with reduced relocation costs. This context provides an ideal setting to develop innovative algorithms that balance the dual roles of facilities as service providers and information sources.

By quantifying the value of information and integrating it into locational models, the project will enable decision-makers to optimise site selection dynamically, adapting to new data and uncertainties. The outcomes will have wide-ranging applications across public services, supply chains, and infrastructure planning, supporting more resilient, sustainable, and cost-effective decisions. Ultimately, this project aims to set a new standard in locational decision-making, driving both academic advancements and real-world impact.