This module is designed to cover:
Type 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.
Total contact hours: 42
Private study hours: 108
Total study hours: 150
Assessment 1 (10-15 hrs) 20%
Assessment 2 (10-15 hrs) 20%
Examination (2 hours) 60%
Reassessment methods:
Like-for-like
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
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.
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