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Details of Grant 

EPSRC Reference: GR/R51377/01
Title: Parallel Algorithms for Worst-Case Modelling, Global Optimisation and Risk Management of Dynamic Systems
Principal Investigator: Rustem, Professor B
Other Investigators:
Darlington, Professor J Asprey, Dr S
Researcher Co-Investigators:
Project Partners:
Department: Computing
Organisation: Imperial College London
Scheme: Standard Research (Pre-FEC)
Starts: 15 October 2001 Ends: 14 October 2004 Value (£): 223,202
EPSRC Research Topic Classifications:
Parallel Computing
EPSRC Industrial Sector Classifications:
Chemicals Financial Services
Energy
Related Grants:
Panel History:  
Summary on Grant Application Form
The project concerns the development of generic algorithms for worst-case modelling, design and risk management of dynamic systems in engineering, economics, and finance. Worst-case modelling is essentially the best model fit to experimental data in view of the worst-case operating condition. Worst-case design for risk management is the best design, decision, or strategy, determined simultaneously with the worst state of the system. The dynamic problems considered are systems of nonlinear differential and algebraic equations solved by software developed in the Centre for Process Systems Engineering at Imperial College. Important software tools include development and efficient parallelisation of global optimisation to identify the global worst-case, nonlinear mixed integer optimisation algorithms for integer design variables and logic-based rules as restrictions.The advantage of worst-case modelling and design is that, for multiple scenarios or rival model specifications, it computes a robust solution. Thus, a basic optimal worst-case performance is assured: actual performance will be non-inferior to this and will improve if any other rival model, or scenario, is realised. The strategy is particularly attractive for safety-critical systems and addresses uncertainty when the worst-case may have too high a cost. This proposal is a shortened version of GR/R29215 in that we have reduced the research in local constrained optimisation algorithms, discrete worst-case design and propose to use existing algoritms and parallelisation to speed-up local search.
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Organisation Website: http://www.imperial.ac.uk