EE4-29 Optimisation (IDX)
Lecturer(s): Prof Alessandro AstolfiAims:
This course introduces finite-dimensional optimisatiom 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.
Syllabus:
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.
Assessment:
One 3-hour exam in April/May
Coursework contribution: 0%
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: None required
Course Homepage: http://www3.imperial.ac.uk/people/a.astolfi/teaching/optimisation
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