Optimisation with Financial Applications - MAST5011
Overview
Formulation/Mathematical modelling of optimisation problems
Linear Optimisation: Graphical method, Simplex method, Phase I method, Dual problems,
Transportation problem.
Non-linear Optimisation: Unconstrained one dimensional problems, Unconstrained high dimensional problems, Constrained optimisation.
Details
Contact hours
Total contact hours: 42
Private study hours: 108
Total study hours: 150
Method of assessment
80% Examination, 20% Coursework
Indicative reading
Guenin, B., Konemann J., and Tuncel, L., A gentle introduction to optimisation, Cambridge University Press, 2004
Winston, W. L., Operations Research: Applications and Algorithms, 4th Edition, Cengage, 2004
Calafiore,G.C., El Ghaoui, L., Optimisation models, Cambridge University Press, 2014
Luenberger D.G, and Yinyu Y., Linear and Nonlinear Programming 4th Edition, Springer 2016
See the library reading list for this module (Canterbury)
Learning outcomes
The intended subject specific learning outcomes. On successfully completing the module students will be able to:
1 demonstrate knowledge and critical understanding of the well-established principles within linear and non-linear programming;
2 demonstrate the capability to use a range of established techniques and a reasonable level of skill in calculation and manipulation of the material to solve problems in the
following areas: linear programming, non-linear programming, approximation methods;
3 apply the concepts and principles in linear and non-linear programming in well-defined contexts beyond those in which they were first studied, showing the ability to
evaluate critically the appropriateness of different tools and techniques;
4 make appropriate use of suitable software.
Notes
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Credit level 5. Intermediate level module usually taken in Stage 2 of an undergraduate degree.
- ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
- The named convenor is the convenor for the current academic session.
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