Course Catalogue

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Optimisation is a common problem faced in engineering, ranging from finding the most efficient solution (e.g., the highest strength structure) to the most economical solution (least cost or carbon emissions). This course covers the mathematical and numerical methods for solving such engineering optimisation problems. The focus is on developing fundamental understanding complemented by ability to solve practical examples.

2 one-hour in-person lectures every week

One-hour in-person tutorial three times in the semester (weeks 2, 4, 8)

Two-hour in-person computer labs two times in the semester (weeks 6 and 10)

Mandatory Entry Requirements:

None

Recommended Entry Requirements :

Background in mathematics and linear algebra is recommended.

Familiarity with a programming language is recommended.

None

None

Assessment

70% Examination

30% Coursework (programming-based solution of optimisation problems)

Reassessment

In accordance with the University's Code of Assessment reassessments are normally set for all courses which do not contribute to the honours classifications. For non honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students, and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions are listed below in this box.

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

This course aims to:

1) develop the ability to mathematically formulate optimisation problems in engineering

2) advance the knowledge of numerical algorithms for solving optimisation problems

3) develop an appreciation of the challenges associated with constrained and multi-objective optimisation

4) establish the tools of variational calculus for deriving Euler-Lagrange equations

5) advance the ability of analysing the computational complexity of algorithms and compare their energy usage

By the end of this course students will be able to:

1) mathematically formulate optimisation problems

2) incorporate observable data to inform models

3) choose appropriate numerical methods to solve a given optimisation problem

4) explain the meaning of the optimisation and model-fitting results

5) derive Euler-Lagrange equations

6) compare different algorithms based on their computational complexity and employ the most appropriate one with least carbon footprint

Students must attend the degree examination and submit all the other components of the course's summative assessment.

Any student who misses an assessment or a significant number of classes because of illness or other good cause should report this by completing a MyCampus absence report.