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Algorithms developed by University of Glasgow researchers have helped NHS Blood and Transplant (NHSBT) tackle the complex problem of increasing the number of kidney transplants in the UK. For people with end-stage renal failure, the most effective form of treatment is transplantation. Dr David Manlove's research team have developed sophisticated algorithms which allow the NHS to help patients who require a kidney transplant, and who have a willing but incompatible donor, to exchange their donor with that of another patient in a similar position, in what is known as a paired exchange. By optimising kidney exchanges, University of Glasgow research has increased the number of transplants from paired donation by 40% between 2008 and 2013, when measured in comparison with the number of transplants that would have been possible with previous pairing techniques. Dr Manlove's work with NHSBT has translated not only into increased quality of life for patients freed from long term dialysis but will also afford the NHS an estimated £16 million of savings over the next 10 years.
Research on designing mathematical methods for optimisation carried out at the University of Southampton has been fundamental to the development of software solutions for transportation problems and has directly led to the growth and commercial success of the niche software company, Logical Transport. Additional beneficiaries are local councils — who have obtained school bus schedules that typically reduced the number of required vehicles by 10-20% and miles driven by 12-15% and have an information management tool for better decision making — and passengers who have experienced improved service quality.
Many operations in daily life, from manufacturing to running a hospital, need to optimise the return on use of resources where volume and value are conditions. Scheduling theory tackles some of the hardest practical optimisation problems, not known to be solvable in reasonable computation time. Strusevich and Kellerer have been able to reformulate practical scheduling challenges as `knapsack problems' - dealing with volume and value constraints - and then design approximation algorithms which can be applied back to the original challenge. The work has attracted EPSRC funding, stimulated a new field of research which is developing fast, been widely published, led to presentations at international conferences including the 2009 Computers and Industrial Engineering conference attended by industry practitioners and is impacting on Combinatorial Optimisation research.
Transport crew scheduling research at Leeds University since 1994 produced optimising algorithms and industry-ready software that led to the spinning out of Tracsis in 2004. The software, including upgrades, is used by over 40 bus and train companies who previously relied on manual processes. A minimum estimate of a £230 million saving in crew costs has been achieved in the UK alone over 2008-31.7.2013. Since 2008, the software has been routinely used by bidders in all UK rail franchise tenders, contributing to cost effective, efficient and reliable rail transport. Success led to the Tracsis floatation in November 2007 (market capitalisation: £46.7 million on 22/5/2013).
Effective industrial design and simulation require efficient and versatile computing systems. As a result of research performed by our team experienced in High Performance Computing (HPC), novel software structures and aligned hardware architectures have led to significant benefits to the energy supply industry and to microprocessor manufacturers.
As a result of our research with supercomputing, simulation times for electric field patterns in power components have reduced more than 30-fold, with accurate complex 3-D outputs for an increased range of configurations, thereby enabling our partner company to achieve results not possible with commercial software and to reduce product development costs by $0.5M - $5M p.a.
Our research has been incorporated by Intel into their numerical libraries and now made available to the general public supported by their latest processor architectures. Intel now has a 82% share of processors, according to the November 2013 Top500 list.