Dr Giacomo Zambelli NAB 3.36

This course is available on the MSc in Applicable Mathematics, MSc in Management Science (Operational Research), MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available as an outside option to students on other programmes where regulations permit.

Students must have a knowledge of linear algebra sufficient to handle matrix inversion and manipulation of partitioned vectors and matrices. Previous experience of computers is not required, but students must be prepared to use computer packages.

To cover the use of mathematical programming models in practice, and an introduction to the theory and computational methods, as described under the headings of the lecture courses below. OR406.1 Foundations of Mathematical Programming: An introduction to the mathematical foundations of mathematical programming OR406.2 Mathematical Programming: Introduction to theory and the solution of linear and nonlinear programming problems: simplex and interior point algorithms, integer linear programming (ILP) methods (branch and bound, enumeration, cutting planes), decomposition methods, quadratic programming.

20 hours of lectures and 15 hours of seminars in the LT.

V Chvatal, Linear Programming; G Dantzig & M Thapa, Linear Programming 1 and 2; M Padberg, Linear Optimization and Extensions; M Bazaraa, J Jarvis & H Sherali, Linear Programming and Network Flows; J Nocedal & S Wright, Numerical Optimization; S Wright, Primal Dual Interior Point Methods; Nemhauser & Wolsey, Integer and Combinatorial Optimization; A Schrijver, Theory of Linear and Integer Programming; J More & S Wright, Optimization Software Guide; H P Williams, Model Building and Mathematical Programming; H P Williams, Model Solving in Mathematical Programming.

Exam (100%, duration: 3 hours) in the main exam period.