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ELEC97063 (EE9-CS3-2) Optimisation

Lecturer(s): Prof Alessandro Astolfi


This course introduces finite-dimensional optimisation theory and the basic algorithms for finding minima.

Learning Outcomes

After the course the student will be able to design computer algorithms for finding minima and maxima in a wide range of optimization problems involving smooth criteria and, just as importantly, to interpret, and if necessary modify, the algorithms found in standard computer packages.


Topics covered include unconstrained optimisation and the associated algorithms of steepest descent and conjugate gradient, Newton methods, rates of convergence, constrained optimisation and the method of Lagrange multipliers, quadratic programming, penalty methods.
A brief introduction to global optimization and integer programming will be also given.
Exam Duration: 3:00hrs
Coursework contribution: 25%

Term: Autumn

Closed or Open Book (end of year exam): Closed

Coursework Requirement:
         To be announced

Oral Exam Required (as final assessment): N/A

Prerequisite module(s): None required

Course Homepage:

Book List:
Please see Module Reading list