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EMTH604-12S2 (C) Semester Two 2012
Unconstrained Optimisation

0.1000 EFTS
09 Jul 2012 - 11 Nov 2012 		↓Other occurrences

Description

Practical and theoretical aspects of the design and development of algorithms for the optimisation of functions of several variables.

This course looks at the minimization of smooth functions of several variables.  The first part of the course examines gradient based methods using line searches, including Newton, quasi-Newton, and conjugate gradient methods.  

A selection of other topics is then introduced, including trust region methods and methods for constrained optimization.  

Demonstration software is used to illustrate aspects of various algorithms in practice.

Topics:
• Gradient based methods: steepest descent, conjugate gradients, Newton's method and quasi-Newton methods. Line searches and trust regions.
• Constrained optimization: Karush-Kuhn-Tucker conditions, quadratic penalty functions, augmented Lagrangians.
• Derivative free methods: positive bases, Clarke's generalized derivative, frames.

Pre-requisites

Subject to approval of the Head of Department.

Course Coordinator / Lecturer

Chris Price (MATH)

Assessment

Assessment Due Date Percentage 
Internal Assessment - TBA 30%
Final Examination 70%

Examination and Formal Tests

Exam Thursday 08 Nov 2012 2:30pm-4:30pm  

Textbooks

Recommended Texts:

• Numerical Optimization, Nocedal and Wright (2006).
• Practical Methods of Optimisation, Fletcher (1987).
• Practical Optimization, Gill, Murray, and Wright (1981).

Fees

Domestic fee $703.00
International fee $3,190.00

Minimum enrolments

This course will not be offered if fewer than 5 people apply to enrol.


For further information see Mathematics and Statistics.

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