Optimisation with Financial Applications - MAST5011

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2022 to 2023
Canterbury
Autumn Term 5 15 (7.5) Eduard Campillo-Funollet checkmark-circle

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.

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.

Notes

  1. Credit level 5. Intermediate level module usually taken in Stage 2 of an undergraduate degree.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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