Project summary:
This project develops dynamic methodologies for multi-stage location decisions that incorporate the value of information. Using Scottish Water's sensor placement challenge as a case study, we aim to optimise decision-making by integrating risk, uncertainty, and real-time data, providing adaptable, sustainable solutions for public services, supply chains, and infrastructure management.
Start date: 1st October 2025
Duration: 36
Funding: Funded
Funding towards:
Funding details: Fully-funded scholarship for 3 years covers all university tuition fees (at UK level) and an annual tax-free stipend. International students are also eligible to apply, but they will need to find other funding sources to cover the difference between the home and international tuition fees. Exceptional international candidates may be provided funding for this difference.
Number of places: 1
Number of places extra: There will be a shortlisting and interview process.
RCUK eligibility: No
Eligibility:
Essential:
- A first- or upper-second-class undergraduate degree (or equivalent) in a relevant field (such as mathematics, computer science, or management science)
- Strong analytical skills and a keen interest in mathematical modelling, decision-making under uncertainty, optimisation, and applications in public services or infrastructure
- Evidence of independent study or research
Desirable
- A strong performance in a Master’s degree in a relevant field.
- Strong written and verbal communication skills
- Ability to work independently and in a multidisciplinary team
More info here: www.strath.ac.uk/studywithus/postgraduateresearchphdopportunities/business/managementscience/insightfulsitingincorporatingthevalueofinformationinlocationdecisions
Study modes eligibility: Full-time, Part-time
Fee status:
Project Details: Use this field to provide further details about the opportunity that aren’t covered elsewhere. This is a chance to expand on the ‘project summary’ field with more in-depth information about the opportunity.
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.
Primary Supervisor: Dr. Thomas Byrne
Additional Supervisor/s: Prof. Matthew Revie
Further information: If there is any further information related to the opportunity you would like to include, please use this space to do so.
