UnitLevel 3Undergraduate

MTH3330 Optimisation and operations research

Faculty of Science

MTH3330 Optimisation and operations research is a level 3, 6-credit-point, undergraduate unit from the Faculty of Science, offered in 2026 in Semester 1 at Clayton and Malaysia. It has no prerequisites and unlocks 2 units.

Credit points
6
Offered in 2026
Semester 1
Clayton, Malaysia
Assessment
Exam 50%
and 1 other task

This is the 2026 handbook entry. See the 2027 entry.

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Requisites

Before MTH3330

No prerequisites or corequisites besides the enrolment rules below.

After MTH3330

2 units list MTH3330 as a prerequisite or corequisite.

Enrolment rules

PREREQUISITE: You must have passed one unit from MTH2051 or MTH3051 or if you are enrolled in the Honours in Econometrics, ETC2440 (this requires manual enrolment).

Alternatively, you must be enrolled in the Master of Mathematics, the Master of Financial Mathematics , or receive special permission from the unit coordinator.

Overview

This unit introduces some of the fundamental concepts and algorithms of mathematical optimisation. Optimisation underpins many parts of both data analytics (machine learning) and business analytics (management science/operations research). The concepts and approaches taught in this unit will be illustrated using examples from both types of analytics, such as training ML models and planning models arising in supply chain optimisation. The unit provides an introduction to the mathematics of continuous optimisation with focus on iterative gradient descent methods, linear programming and network optimisation. It covers both the underpinning theory, such as convergence analysis and duality, and the practical implementation of optimisation algorithms.

Offerings in 2026

Teaching periodCampusMode
First semesterClaytonOn campus
First semesterMalaysiaOn campus

Assessment

  • Continuous assessmentDemonstration
    50%
  • Final assessment - Exam (3 hours and 10 minutes)Examination
    50%

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. 1

    Explain and apply the mathematical theory of optimisation, including optimality conditions, iterative algorithms for nonlinear problems, and the principles of duality and non-smooth optimisation;

  2. 2

    Formulate and analyse optimisation problems arising in machine learning, operations research, and network optimisation, selecting and justifying appropriate algorithms;

  3. 3

    Implement and evaluate linear programming and related optimisation algorithms, proving optimality where appropriate and applying them to real-world data and applications;

  4. 4

    Communicate optimisation reasoning and results effectively, both orally and in writing, and collaborate in small groups to solve problems.

Workload and teaching

  • Workshops36 hours
  • Applied sessions22 hours
  • Teaching approachActive learning
  • Two 1.5-hour workshops;
  • One 2-hour applied class (in weeks 2-12) and
  • 7 hours of independent study per week.
 

Active learning will occur in lectures and applied classes.

Learning resources

Required resources

Most of the content of this unit is covered in the following two textbooks:
1. Luenberger & Ye, “Linear and nonlinear programming” 2016 (4th edition).
2. Nodeal & Wright "Numerical Optimization" 2006 (2nd edition)
Both of these are available electronically from the library.

Technology resources

Computer for completing computational exercises.

Where it fits

MTH3330 is part of 8 areas of study in the 2026 handbook.

Contacts

Unit Coordinators
Professor Andreas Ernst
Dr Kevin Yuen
Chief Examiners
Professor Andreas Ernst

Common questions

What are the prerequisites for MTH3330?

MTH3330 has no prerequisites, but enrolment rules apply.

What can I take after MTH3330?

MTH3330 is a prerequisite or corequisite for 2 units, including MTH4333 and MTH5333.

When is MTH3330 offered?

In 2026, MTH3330 runs in Semester 1 at Clayton and Malaysia.

Does MTH3330 have an exam?

Yes. The exam is worth 50% of the final mark, alongside 1 other task.

Which majors and minors include MTH3330?

MTH3330 is part of Applied mathematics; Business analytics; Financial and insurance mathematics; Mathematical statistics; and Mathematics, and 1 other area of study.

More details

Credit points
6
Level
3
Study level
Undergraduate
Faculty
Faculty of Science
Organisational unit
School of Mathematics
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 1
Study abroad
Available