School of Mathematics

MSc Operational Research with Computational Optimization

Why Operational Research with Computational Optimization?

Studying Operational Research with Computational Optimization will give you the opportunity to develop skills in the mathematical theory of methods for optimization and their implementation using techniques of formal programming and high performance computing. You will also learn how to formulate and solve practical problems.

A graduate of this programme would be very attractive to companies who develop their own high performance optimization software and also to firms who are embedding optimization methods into their products. The MSc would also provide an ideal background for PhD studies in this area.

The School of Mathematics at the University of Edinburgh has an exceptionally strong Computational Optimization group. It contains world-class experts in linear, integer, quadratic, nonlinear, convex, nonconvex, global, stochastic, parallel and distributed programming. Group members are especially interested in interior-point methods, parallel simplex methods, advanced integer programming techniques, meta-heuristics, and modern first- and second-order algorithms, with applications ranging from finance, logistics, and manufactring to electricity and oil markets, compressed sensing, and airline ticket pricing.


Structure and course options for the Operational Research with Computational Optimization MSc programme

You will take 120 credits of courses in total during Semesters 1 and 2, followed by a 60 credit dissertation which you complete over the summer. The courses you take will be dependent on the availability of courses each year which may be subject to change as the curriculum develops to reflect a modern degree programme.