This research area covers the development and application of advanced analytical methods to support improved decision making, especially in relation to the operation of complex and uncertain systems.
This research area covers the development and application of advanced analytical methods to support improved decision-making, especially in relation to the operation of complex and uncertain systems. These methods draw heavily on mathematics, statistics and computer science and include, for example:
- data analysis
- stochastic processes
- computational research.
Research in this area may incorporate aspects of complexity science.
Applications include, for example:
- manufacturing, service and supply chain operations including the circular economy
- telecommunications and networks
- policy modelling
- environment and energy
- resource efficiency
- security and defence
- revenue management
- financial engineering
- reliability and maintenance.
This is a new, cross-cutting research area encompassing Mathematical Aspects of Operational Research, Engineering Approaches to Manufacturing Operations and elements of Transportation Operations and Management. There are also relevant research areas in the Information and communication technologies (ICT) theme which link to this area, especially the Artificial intelligence technologies research area.
This new research area will bring together development of new techniques and methodologies with their application areas, promoting a unified approach and synergistic working across the community.
The UK already plays a leading role in advancing a number of core analytical methods (for example optimisation and data analytics). We aim to build on this by supporting development of the underpinning techniques of operational research, and promoting their impact by strengthening links between application areas and users.
We have four objectives.
Building on UK strength
Our objective is to have a portfolio in this area that builds on UK strength in core methodologies, as well as new applications of these techniques in a range of challenge and outcome driven situations. We will invest in research that focuses on cross-cutting challenges, in particular enabling real time decision making under uncertainty and dealing with complex or poor-quality data.
We aim to have sufficient people with skills in operational research, particularly at the early career stage, to meet demand across a wide range of domains.
Global challenges research fund
Our objective is to have invested in research supporting the goals of the Global Challenges Research Fund.
Our objective is to have built on the Operational Research Theme Day and developed links with the Operational Research (OR) Society, the Alan Turing Institute, industry and users looking at applications and at connections with underpinning analytical methods.
Researchers in this area will play a central role in the Grand Challenge of Big Data, as well as contributing to other EPSRC priorities. To maximise impact, they need to ensure effective communication with researchers in other contributing areas, including statistics, artificial intelligence, machine learning and numerical analysis.
Collaborative working with businesses and end-users is critical to ensure research is informed by real-world problems.
To support the creation of this new research area, EPSRC will work across themes and with relevant external stakeholders to ensure the published strategy reflects the needs of all interested communities, and will actively monitor changes to this area’s portfolio.