Dr Nikolaos Argyris, NAB3.20

The course is compulsory for MSc Management Science (Operational Research). Optional course for MSc Applicable Mathematics and as an outside option for students on other degrees where regulations permit.

Students must have a knowledge of mathematics and statistics to the level of the undergraduate papers MA107 Quantitative Methods and Elementary ST102 Statistical Theory. Students must be prepared to use computer packages.

Mathematical Programming is one of the most powerful and widely-used quantitative techniques for making optimal decisions. The course has a pragmatic focus and aims at enabling students to model and solve real-life management problems. In providing an overview of the most relevant techniques of the field, it teaches a range of approaches to building Mathematical Programming models and shows how to solve them and analyse their solutions.

Content includes:

An introduction to the theory of linear programming. The modelling life cycle and modelling environments. Formulation of management problems using linear and network models; solution of such problems with a special-purpose programming language; interpretation of the solutions; limitations of such models. Formulation and solution of non-linear models including some or all of binary, integer, convex and stochastic programming models

OR428 18 MT, OR428.A 18 MT, computer workshops 9 x 2-hours MT (optional)

Students will have the opportunity to submit a mock project for marking and comment before the final assessed project is due.

Central to the course is: H P Williams, Model Building in Mathematical Programming, Wiley. A good introduction to Mathematical Programming provide the relevant chapters of: F S Hillier and G J Liebermann: Introduction to Operations Research, McGraw-Hill. A more theoretical treatment can be found in: D Bertsimas and J N Tsitsiklis: Introduction to Linear Optimization, Athena Scientific. Further suggestions for reading are given during the course.

This course is examined entirely by weekly exercises and/or by project. Written work is marked on presentation as well as on content.