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Department of Mathematical Sciences, Unit Catalogue 2009/10


MA50087: Optimisation methods of operational research

Click here for further information Credits: 6
Click here for further information Level: Masters
Click here for further information Period: Semester 1
Click here for further information Assessment: CW 25%, EX 75%
Click here for further informationSupplementary Assessment: Like-for-like reassessment (where allowed by programme regulations)
Click here for further information Requisites:
Description:
Aims & Learning Objectives:
Aims:
To present methods of optimisation commonly used in OR, to explain their theoretical basis and give an appreciation of the variety of areas in which they are applicable. To facilitate an in-depth understanding of the topic.
Objectives: On completing the course, students should be able to:
* Recognise practical problems where optimisation methods can be used effectively.
* Implement appropriate algorithms, and understand their procedures.
* Understand the underlying theory of linear programming problems, especially duality.
* Demonstrate an in-depth understanding of the topic.

Content:

* The Nature of OR: Brief introduction.
* Linear Programming: Basic solutions and the fundamental theorem. The simplex algorithm, two phase method for an initial solution. Interpretation of the optimal tableau. Applications of LP. Duality.
* Topics selected from: Sensitivity analysis and the dual simplex algorithm. Brief discussion of Karmarkar's method. The transportation problem and its applications, solution by Dantzig's method. Network flow problems, the Ford-Fulkerson theorem.
* Non-linear Programming: Revision of classical Lagrangian methods. Kuhn-Tucker conditions, necessity and sufficiency. Illustration by application to quadratic programming.
NB. Programmes and units are subject to change at any time, in accordance with normal University procedures.