Advanced Optimisation

Undergraduate | 2026

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Area/Catalogue
MATH X302
Course ID icon
Course ID
207616
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course level icon
Course level
3
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Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
Yes
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
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Note:
Course data is interim and subject to change

Course overview

This course examines nonlinear mathematical formulations and concentrates on convex optimisation problems. Many modern optimisation methods in areas such as design of communication networks and finance rely on the classical underpinnings covered in this course.

Course learning outcomes

  • Demonstrate understanding of the complexities of, and techniques for solving, nonlinear optimisation problems
  • Apply algorithms to solve both constrained and un-constrained one-dimensional optimisation problems
  • Apply algorithms to solve multi-dimensional unconstrained optimisations problems
  • Apply algorithms to solve convex constrained optimisation problems
  • Apply heuristic methods to solve non-convex problems and evaluate the limitations of such approaches
  • Implement computer code for the algorithms studied throughout the course and critically analyse and interpret the results

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A