Course Catalogue

Optimisation Methods and Applications UESTC5041

  • Academic Session: 2026-27
  • School: School of Engineering
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 1
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

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 practical examples.

Timetable

20 hour in-person lectures

One-hour in-person tutorial three times in the semester

Two-hour in-person computer labs two times in the semester

Requirements of Entry

Mandatory Entry Requirements

None

 

Recommended Entry Requirements :

Background in mathematics and linear algebra is recommended.

Familiarity with a programming language is recommended.

Excluded Courses

None

Co-requisites

None

Assessment

Assessment

70% Examination

30% Coursework

Main Assessment In: December

Course Aims

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.

Intended Learning Outcomes of Course

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.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course’s summative assessment. In cases where the assessment comprises more than 75% of the course weighting (for example, 100% weighting dissertation), students must submit this assessment in order to meet the minimum requirement for the award of credit.