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This study demonstrates how Bayes linear methodologies developed at Durham University have impacted on industrial practice. Two examples are given. The approach has been applied by London Underground Ltd. to the management of bridges, stations and other civil engineering assets, enabling a whole-life strategic approach to maintenance and renewal to reduce costs and increase safety. The approach has won a major award for innovation in engineering and technology. The methodology has also been applied by Unilever and Fera to improve methods of assessing product safety and in particular the risk of chemical ingredients in products causing allergic skin reactions.
Research in the HWCS Intelligent Systems Lab since 2006 has developed approaches to accelerate and improve large-scale optimization. This has led to new algorithms that enable multiple high-quality solutions for complex problems, either more quickly, with better solution quality than previously obtainable, or both. These algorithms, combined with uncertainty quantification techniques from related research, have been adopted by both British Petroleum Plc (BP) and Epistemy Ltd (an SME serving the oil/gas sector). Impact for BP includes improved business decision-making (relating to ~$330M in turnover),and impact for Epistemy includes sales of £230k.
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.
Prof. Pennanen and collaborators have developed mathematical models and computational techniques for financial risk management. The techniques allow for quantitative analysis and optimization of financial risk management actions in an uncertain investment environment. The techniques have been used by the State Pension Fund, Ministry of Social Affairs and Health, Bank of Finland and Pension Policy Institute. The techniques have significant impact on practitioners and professional services in increasing the awareness and understanding of long-term financial risks that are difficult to quantify with more traditional techniques. Beneficiaries of the developed risk management techniques include future pensioners and tax payers.
A generalized additive model (GAM) explores the extent to which a single output variable of a complex system in a noisy environment can be described by a sum of smooth functions of several input variables.
Bath research has substantially improved the estimation and formulation of GAMs and hence
This improved statistical infrastructure has resulted in improved data analysis by practitioners in fields such as natural resource management, energy load prediction, environmental impact assessment, climate policy, epidemiology, finance and economics. In REF impact terms, such changes in practice by practitioners leads ultimately to direct economic and societal benefits, health benefits and policy changes. Below, these impacts are illustrated via two specific examples: (1) use of the methods by the energy company EDF for electricity load forecasting and (2) their use in environmental management. The statistical methods are implemented in R via the software package mgcv, largely written at Bath. As a `recommended' R package mgcv has also contributed to the global growth of R, which currently has an estimated 1.2M business users worldwide [A].
The safe operation of ships is a high priority task in order to protect the ship, the personnel, the cargo and the wider environment. Research undertaken by Professor Alexander Korobkin in the School of Mathematics at UEA has led to a methodology for the rational and reliable assessment of the structural integrity and thus safety of ships and their cargos in severe sea conditions. Central to this impact is a set of mathematical models, the conditions of their use, and the links between them, which were designed to improve the quality of shipping and enhance the safety of ships. The models, together with the methodology of their use, are utilised by the ship certification industry bringing benefits through recognised quality assurance systems and certification.
Many organisations rely on increasingly large and complex datasets to inform operational decision- making. To assist decision-makers when decisions are data-driven, computational tools are needed that present reliable summary information and suggest options allied to the key objectives of decision-making. Research at RGU has developed novel learning and optimisation algorithms driven by multifactorial data and implemented this in commercial decision-support software. The research has had economic impact by providing products to be sold: drilling rig selection tool (ODS-Petrodata Ltd.) and subsea hydraulics diagnostic tool (Viper Subsea Ltd.). Further economic impact comes from operations management software developed for British Telecom.
The WinBUGS software (and now OpenBUGS software), developed initially at Cambridge from 1989-1996 and then further at Imperial from 1996-2007, has made practical MCMC Bayesian methods readily available to applied statisticians and data analysts. The software has been instrumental in facilitating routine Bayesian analysis of a vast range of complex statistical problems covering a wide spectrum of application areas, and over 20 years after its inception, it remains the leading software tool for applied Bayesian analysis among both academic and non-academic communities internationally. WinBUGS had over 30,000 registered users as of 2009 (the software is now open-source and users are no longer required to register) and a Google search on the term `WinBUGS' returns over 205,000 hits (over 42,000 of which are since 2008) with applications as diverse as astrostatistics, solar radiation modelling, fish stock assessments, credit risk assessment, production of disease maps and atlases, drug development and healthcare provider profiling.
This statement details the impact of research undertaken by members of the Logistics and Operational Research Group (LORG) at the University of Portsmouth in the area of strategic financial investment portfolio selection. A set of goal programming models was developed, which for the first time allowed the investment fund managers to consider a wider range of objectives beyond the usual risk and return paradigm. As a result, the decision making capabilities of key investment fund managers and advisors including those working for the Kuwait Sovereign Wealth Fund were enhanced, resulting in improved decision making capabilities.
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.