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 sufficient knowledge of linear algebra (linear independence, determinants, matrix inversion and manipulation) and of basic multivariate calculus (derivatives and gradients). Previous experience of computers is not required.

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.

MG4C6.1 Foundations of Mathematical Programming: An introduction to linear programming and to the theory of duality.

MG4C6.2 Mathematical Programming: Introduction to theory and the solution of linear and nonlinear programming problems: basic solutions and the simplex method, convex programming and KKT conditions, integer linear programming methods (branch and bound and cutting cutting planes).

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

A reading week will take place in W6. There will be no teaching during this week.

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.