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The use of goal programming to optimise resource allocation in hospitals in the UK and China

Summary of the impact

Managers of hospital units are required to allocate medical resources in accordance with, sometimes conflicting, objectives and performance targets and against continual variations in patient flow, staff and bed availability. The Logistics and Operational Research Group (LORG) at the University of Portsmouth has developed novel models, based on a combination of discrete event simulation, multi-phase queuing theory, and goal programming, that have improved the understanding of ward logistics by hospital managers in the UK and China, enabling them to make changes that have improved the efficiency of bed allocation, patient flow and allocation of medical resources and improved outcomes for patients.

Submitting Institution

University of Portsmouth

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Economic

Research Subject Area(s)

Mathematical Sciences: Applied Mathematics, Statistics
Information and Computing Sciences: Information Systems

Case Study 3: Applications of Computational Optimization under Uncertainty in Decision Support (Computational Optimization)

Summary of the impact

The Computational Optimization Group (COG) in the Department of Computing produced new models, algorithms, and approximations for supporting confident decision-making under uncertainty — when computational alternatives are scarce or unavailable. The impact of this research is exemplified by the following:

  1. Axioma (a firm that provides factor-based risk models and portfolio construction tools for equity investors) now offers insurance to equity portfolios with efficient calculation of coherent risk measures — allowing diverse assets in portfolios.
  2. Commerzbank now has improved risk management for proprietary indices used in funds and options, increasing their revenue of investment strategies.
  3. The consultancy Decision Tree uses scenario tree based valuation of swing options to create better decision-support software, which attracted new clients in the energy sector.
  4. The utility provider Trianel now saves over two million Euros annually by adopting tools that rely on our new optimization techniques.
  5. The energy trading company e&t bought software based on our research that optimizes coal procurement contracts for a 750MW coal-fired power plant.

Submitting Institution

Imperial College London

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Applied Mathematics, Numerical and Computational Mathematics, Statistics

UOA11-04: Semmle: a powerful query language for analysing large data sources

Summary of the impact

Semmle is a successful spin-out company set up by members of the UoA, based on their research on program analysis. Semmle markets an industrial-strength product allowing organisations with large software systems to understand and manage their code bases. This business intelligence platform started to be sold to prominent customers in 2008, including [text removed for publication] NASA. NASA used it to help ensure the safe landing of the Curiosity Mars Rover.

Submitting Institution

University of Oxford

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Computation Theory and Mathematics, Computer Software
Psychology and Cognitive Sciences: Cognitive Sciences

Improving modelling and forecasting in the public and private sectors

Summary of the impact

A series of econometric methods and software, designed by a team of econometricians at Oxford, have been adopted as standard by a large range of governmental bodies, international agencies and businesses. The econometric methods are designed to model and forecast high-dimensional, evolving economic processes facing multiple structural shifts, while the econometric software (PcGive) implements the resulting best-practice procedures. The application of these methods have resulted in more appropriate empirical models, improved robust forecasts, and, consequently, better decision making by these bodies.

Submitting Institution

University of Oxford

Unit of Assessment

Economics and Econometrics

Summary Impact Type

Economic

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Information Systems
Economics: Econometrics

The Development of Commercial Optimization Software

Summary of the impact

Research led by Professor Roger Fletcher has resulted in the development of a suite of algorithms that are now widely used throughout industry. An algorithm of fundamental importance constructed by Fletcher and co-workers is the filter method — a radically different approach to solving large and complex nonlinear optimization problems typical of those faced by industry. This algorithm was developed with the principal aim of providing a computationally reliable and effective method for solving such problems. The filter method is now utilised by a variety of high-profile industry end-users including IBM, Schlumberger, Lucent, EXXON, Boeing, The Ford Motor Company, QuantiSci and Thomson CSF. The use of the filter method has had a significant economic and developmental impact in these companies through enhanced business performance and cost savings.

Submitting Institution

University of Dundee

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Applied Mathematics, Numerical and Computational Mathematics
Information and Computing Sciences: Computation Theory and Mathematics

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