Optimisation with Financial Applications - MA5511

Location Term Level Credits (ECTS) Current Convenor 2019-20
Canterbury Autumn
View Timetable
5 15 (7.5) DR M Kalli


Pre-requisite: MAST4005: Linear Mathematics, MAST4006 : Mathematical Methods 1, MAST4007: Mathematical Methods 2, and MAST4003: Introduction to Finance or MAST4013: Financial Mathematics.





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.


This module appears in:

Contact hours

42 hours

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 Programmingm 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.

The intended generic learning outcomes. On successfully completing the module students will be able to:

Demonstrate an increased ability to:
1 manage their own learning and make use of appropriate resources;
2 understand logical arguments, identifying the assumptions made and the conclusions drawn;
3 communicate straightforward arguments and conclusions reasonably accurately and clearly;
4 manage their time and use their organisational skills to plan and implement efficient and effective modes of working;
5 solve problems relating to qualitative and quantitative information;
6 make use of information technology skills such as appropriate software, online resources (moodle), internet communication;
7 communicate technical material competently;
8 demonstrate an increased level of skill in numeracy and computation.

University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.