The course has 2 lectures a week, 1 lab a week (offered at two different times) and a drop-in section. To see the their schedule and location, visit the time tabling website.

The course activities include:

The lectures provide the core of the course material. The lectures will cover theoretical concepts of optimisation, but also some practical examples. Some lectures will have problem solving sessions, where the modelling and coding of optimisation problems and algorithms will be demonstrated. The drop-in sessions provide an opportunity to ask targeted questions and provide feedback. Finally, the labs are where you put your new skills into practice while getting one-on-one support from the tutors.


The schedule below is preliminary and may change based on the feedback we get from students. The schedule indicates the content of each lecture. The slides and videos of each lecture can be found in lectures.

For the labs, the schedule below indicates what problem sets will be worked on and some recommend questions to work on during that session.

Week Dates Lecture A Lecture B Labs A/B
1 24/7 - 28/7 01-course-overview
02-LP-modelling -
2 31/7 - 4/8 03-LP-feasibility
04-LP-simplex LP: Q1,11,12
3 7/8 - 11/9 05-LP-approximations
4 14/8 - 18/8 07-MIP-branch 08-MIP-cutting MIP: Q2,4,7
5 21/8 - 25/8 09-cvx-convexity 10-cvx-optimisation
6 28/8 - 1/9 11-cvx-interior 12-minizinc CVX: Q2,5,8
7 18/9 - 22/9 13-construction 14-local-search MiniZinc
8 25/9 - 29/9 15-metaheuristics-1 16-metaheuristics-2 MiniZinc
9 2/10 - 6/10 Holiday 17-cp-lns
Local Search
10 9/10 - 13/10 18-network-flow 19-path-planning Metaheuristics
11 16/10 - 20/10 20-decomp-column-gen 21-decomp-benders Metaheuristics
12 23/10 - 27/10 Guest Lecture A
Guest Lecture B
Exam preparation


The material of the lectures can be found in the cloudstor:

The slides and videos will be uploaded to the cloudstor, according to the schedule described above. The slides will be provided before the lectures. The videos will be provided after the lectures.

Drop-in sessions

If you have an administrative question or question about the course content or assessments, this is a good opportunity for you meet with the lecturers and tutors.

Computer labs

The labs are where you put your knowledge into practice, to solve problems and get one-on-one help from the tutors. Both computer labs will be on-campus. There is no need to sign up. If you have a clash and can’t attend the appropriate session, you may join the other.

The labs are structured around the problem sets for each topic, each of which covers around two weeks of labs. After one week covering a problem set, the solutions will be pushed to the repository. Tutors will also present solutions during the lab as the problems are covered.

In addition to the problem sets, bring along any questions you have in regards to assignments or concepts covered in lectures. The tutors are there to clarify any confusion, and to help you develop your theoretical understanding and technical skills. However, they are not there to provide strong hints or to direct you in the process of doing assignments.

Come along prepared. If you haven’t been regularly attending / watching lectures, don’t expect the tutors to cover the relevant material for you in the labs.

See deliverables for details of the participation marks associated with labs.

Updated:    11 Oct 2023 / Responsible Officer:    Director, School of Computing / Page Contact:    Felipe Trevizan