The module descriptors for our undergraduate courses can be found below:

  • Four year Aeronautical Engineering degree (H401)
  • Four year Aeronautical Engineering with a Year Abroad stream (H410)

Students on our H420 programme follow the same programme as the H401 spending fourth year in industry.

The descriptors for all programmes are the same (including H411).


Optimisation IDX S5

Module aims

The aim of this module is to equip you with the tools to formulate and solve general constrained and unconstrained optimisation problems. The module covers several introductory topics in optimisation such as necessary and sufficient conditions of optimality, basic optimization algorithms (gradient, Newton, conjugate directions, quasi-Newton), Kuhn-Tucker conditions, penalty method, recursive quadratic programming, and global optimization. Each topic is covered in a mathematical rigorous way with attention to regularity, convergence conditions, and complexity.  

The module assumes prior basic calculus and linear algebra knowledge such as multivariable calculus, sequences, compactness, and eigenvalues.

Learning outcomes

Upon successful completion of this module, you will be able to:
1 - Formulate simple unconstrained and constrained optimization problems
2 - Classify optimal solutions
3 - Apply the correct methods to solve such problems
4 - Write basic unconstrained optimization algorithms and assess their convergence and numerical properties
5 - Apply the notion of penalty in the solution of constrained optimization problems
6 - Change constrained optimization problems into equivalent unconstrained problems
7 - Apply basic algorithms for the solutions of global optimization problems

Module syllabus

Necessary and sufficient conditions of optimality
Line search
The gradient method, Newton's method, conjugate direction methods, quasi-Newton methods, methods without derivatives
Kuhn-Tucker conditions
Penalty function methods
Exact methods
Recursive quadratic programming
Global optimization

Teaching methods

This module is taught as a traditional module with theoretical lectures supported by exercises and examples. 
The lectures cover the topics from a theoretical point of view. Concepts, problems and solution methods are explained and justified from a theoretical and intuitive point of view. The  coursework is an application of some of the methods seen in the module to a well-known optimization problem.
The module makes use of a set of  lecture notes which contains all material taught in the lectures and over 100 exercises.


A final exam (3hrs written examination in the Summer term) will test the theoretical concepts covered during the lectures (75%).
Formative feedback will be provided on an ongoing basis: in the classroom (as general comments) and during office hours.

Module leaders

Professor Alessandro Astolfi