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Computational optimisation, also known as numerical optimisation, has the wide and growing use in science, engineering, economics, and industry. Important topics include continuous optimisation, global optimisation, integer programming, matrix optimisation, multi-objective optimisation, network optimisation, nonsmooth optimisation, and stochastic optimisation.

We have a number of PhD students working in this field on topics ranging from modelling and optimising multi-hop wireless telephone networks to the use of optimisation techniques in mathematical finance. Much of the work has been supported by various outside organisations and carried out with their collaboration. Recent examples include the European Space Agency, ThyssenKrupp, Alcatel-Lucent, Bell Labs, Qualcomm, Brussels Capital-Region, EPSRC etc. Within Mathematics, computational optimisation is researched by Maria Battarra, Joerg Fliege, Tri-Dung Nguyen, and Hou-Duo Qi.

Project Overview

Particular contributions to the academic literature include correlation stress testing for Value at Risk and its application in finance, stochastic programming and equilibrium models for problems arising from areas such as competition in electricity markets, transportation, risk management and supply chains, algorithms for power control and routing in wireless networks, numerical methods for multiobjective (multicriteria) optimisation, developments in linear/nonlinear semidefinite programming and matrix completion problems, best shape-preserving spline interpolation, algorithmic approaches to nonsmooth optimisation, exact and approximation methods for solving problems arisen in combinatorial auctions and algorithmic game theory etc. Please see the individual project pages and individual member of staff pages for further information.

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