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, modelling, optimisation, forecasting, simulation, data analysis, stochastic processes and computational research. Research in this area may incorporate aspects of complexity science.
Applications include, for instance: manufacturing, service and supply chain operations including the circular economy; healthcare; transportation; telecommunications and networks; policy modelling; environment and energy; resource efficiency; security and defence; revenue management; financial engineering; logistics; and 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 Information and Communication Technologies (ICT) which link to this area, especially Artificial Intelligence Technologies.
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 (e.g. 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.
By the end of the current Delivery Plan, 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
- Sufficient people with skills in Operational Research, particularly at the early-career stage, to meet demand across a wide range of domains
- Invested in research supporting the goals of the Global Challenges Research Fund (GCRF)
- Built on the Operational Research Theme Day and developed links with the 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 (e.g. 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.Highlights:
Operational Research plays a vital role in the UK economy and society, underpinning a wide range of industries and public services and identified as having a leading role in meeting key challenges in all four EPSRC Outcomes. Reflected in the 2012 Deloitte report and at a 2012 OR Society workshop, for instance (Evidence source 1,2), this importance to the economy is also highlighted in EPSRC's portfolio in this area, a very large majority of which is relevant to one or more industrial sectors (e.g. manufacturing, healthcare, financial services and ICT). Operational Research is linked to many EPSRC research areas and Themes, evidenced by the majority of funded proposals being co-funded.
In the UK, Operational Research has remained close to its interdisciplinary roots and has a worldwide reputation for its application focus and impact. Looking forward, it is expected to play an even greater role in manufacturing, given the emergence of ‘the fourth industrial revolution’ and the transition from products to through-life services (Evidence source 1-7).
In recognition of connections across the EPSRC portfolio and the outcomes of the EPSRC Operational Research Theme Day, there have been changes to the definition of Operational Research – not least to better reflect the entire research community in this field. It is important that the balance of this area’s portfolio is maintained, to ensure it meets the needs of the community and the UK, including the driving of research by methods and applications.
Researchers in this field have a broad range of skills (e.g. optimisation techniques, scheduling, modelling and forecasting) and there is demand from industry to recruit researchers with fundamental knowledge of methodology. While there is the threat of key capacity being lost from academia to industry, UK universities have the opportunity to complement industry’s research interests rather than trying to replicate them, and we need to support academics at early-career stages to enable career progression (Evidence source 1-7).
The research area is of substantial relevance to the Productive, Healthy, Connected, and Resilient Nation Outcomes, with short, medium and long-term contributions. It contributes significantly to the following Ambitions:
P3: Establish a new place for industry that is built upon a ‘make it local, make it bespoke’ approach
This research area is expected to be a key discipline, contributing to scheduling, creating new models for industry, introducing innovative products and producing smart tools and technologies.
P4: Drive business innovation through digital transformation
Development and implementation of new technologies will transform business models, supply chains and services.
H3: Optimise diagnosis and treatment
This research contributes to development of optimised models that will support decision-making for personalised treatments.
H5: Advance non-medicinal interventions
This research area can contribute through its role in data analytics, as well as dynamic and real-time decision making.
C1: Enable a competitive, data-driven economy
Contributes specifically to the use of novel mathematics and statistics techniques and translating these to realise benefits to business through forecasting and decision-making.
R4: Manage resources efficiently and sustainably
This research area develops models, optimises systems and makes decisions for supply chain operations.
- Deloitte, Measuring the Economic Benefits of Mathematical Science Research in the UK (PDF), (2012)
- Operational Research (OR) Society, Making an Impact, (2012)
- EPSRC, Operational Research Theme Day Report (PDF), (2015)
- Research Excellence Framework (REF) 2014 exercise, Overview Report by Main Panel B and Sub-panels 7-15 (PDF), (2014)
- International Review of Mathematical Sciences (PDF), (2010)
- World Health Organization (WHO), Meeting Global Health Challenges through Operational Research and Management Science, (2011)
- National Health Service, Five Year Forward View (PDF), (2014)
Research area connections
This diagram shows the top 10 connections between Research Areas within the EPSRC research portfolio. The depth of the segment relates to value of grants and the width of the segment relates to the number of grants shared by those two Research Areas. Please click to see the related Research Area rationale.
Visualising our Portfolio (VoP)
Visualising our portfolio (VoP) is a tool for users to visually interact with the EPSRC portfolio and data relationships.
EPSRC support by research area in Operational research (GoW)
Search EPSRC's research and training grants.