MTH4331 Nonlinear optimisation
Faculty of Science
MTH4331 Nonlinear optimisation is a level 4, 6-credit-point, postgraduate unit from the Faculty of Science. It isn't offered in 2026. It has no prerequisites.
- Credit points
- 6
- Offered in 2026
- Not offered
- Assessment
- Exam 50%
- and 1 other task
The 2027 handbook has no page for MTH4331. This is its 2026 entry, the latest one.
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Requisites
Before MTH4331
No prerequisites or corequisites besides the enrolment rules below.
After MTH4331
No unit lists MTH4331 as a prerequisite in the 2026 handbook.
Equivalent units
The same content under another code. Only one of them counts.
Overview
This unit covers the theory of nonlinear optimisation, numerical methods for solving unconstrained and constrained nonlinear optimisation problems, and the mathematical theory of why these methods work. Their behaviour is explored in programming exercises using Matlab.
Topics covered include convexity, necessary and sufficient optimality conditions, gradient descent, Newton’s method, globalised Newton, inexact Newton, quasi Newton, trust-region Newton, projected gradient descent, Newton-Lagrange iteration, penalty methods, and SQP methods.
Offerings in 2026
The 2026 handbook lists no offerings for MTH4331.
Assessment
- Continuous assessmentDemonstration50%
- Final assessment - Exam (3 hours and 10 minutes)Examination50%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Demonstrate an advanced understanding of nonlinear optimisation theory at a conceptual level as well as at a granular level;
- 2
Demonstrate an advanced understanding of the uses of common numerical methods for solving unconstrained and constrained optimisation problems, as well as their advantages and disadvantages;
- 3
Apply mathematical principles and theorems to quantify how fast and in what sense these numerical methods converge;
- 4
Implement numerical methods for nonlinear optimisation problems in Matlab;
- 5
Select and apply numerical methods for nonlinear optimisation problems in a real-world context;
- 6
Communicate concepts and arguments related to nonlinear optimisation.
Workload and teaching
- Applied sessions12 hours
- Seminars36 hours
- Teaching approachActive learning
- Two 1.5 -hour seminars;
- One bi-weekly 2-hour applied class (commencing in week 2) and
- 8 hours of independent study per week.
Active learning will occur in lectures and applied sessions.
Contacts
- Unit Coordinators
- Dr Janosch Rieger
- Chief Examiners
- Dr Janosch Rieger
Common questions
What are the prerequisites for MTH4331?
MTH4331 has no prerequisites, but enrolment rules apply.
When is MTH4331 offered?
MTH4331 has no offerings listed in the 2026 handbook.
Does MTH4331 have an exam?
Yes. The exam is worth 50% of the final mark, alongside 1 other task.