This project aims to predict the best optimisation approach for large scale, typically hierarchical, optimisation problems where the objective function is expensive to evaluate. The project will compare a range of approaches to optimisation with an emphasis on methods using sequential approximation to the objective function. The ultimate aim is to produce a library of optimisation subroutines using emulators that could be incorporated into other engineering software.

In June 2008, a workshop on optimisation of expensive function was held to explore the wider industrial applications of methods researched in this project.

Project staff and support

Jari Fowkes (Postgraduate Associate, University of Oxford)
Nick Gould (Academic supervisor, University of Oxford)
Chris Farmer (Industrial supervisor, Schlumberger)
Tim Boxer (Technology Translator, Industrial Mathematics KTN)

This project is being carried out at the University of Oxford, in conjunction with Schlumberger. It is supported by an EPSRC industrial CASE award, made available through the Knowledge Transfer Network for Industrial Mathematics. Start date: September 2007; duration: 3.5 years.