COMP4691/8691 Optimisation
Optimisation is the art and practice of making good decisions. Optimisation technology supports humans and society in this endeavour, and enables the design and operation of automated systems. It plays a particularly important role in robotics, artificial intelligence and machine learning as well as more traditional industries such as mining, energy, transport, logistics, manufacturing and finance.
While at first the thought of optimising a system might sound rather dry and tedious, don't be fooled! In practice is often extremely fun and fulfilling. There is no shortage of challenge and insight: from translating a real-world system into a mathematical model, designing specialised algorithms for solving the problem, and then exploring and interpreting the outcomes.
Semester 2, 2026. See prerequisites and requirements under Programs and Courses for COMP4691 and COMP8691.
Staff
- Course convener and lecturer
- Felipe Trevizan
- Tutor
- Jiawen Wang
Learning outcomes
By the end of the course you'll be able to:
- Apply linear programming and mixed-integer programming models to solve real-world problems.
- Recognise and formulate convex optimisation problems arising in practice.
- Explain the theoretical foundations of convex optimisation and use them to characterise optimal solutions.
- Define an appropriate local search neighbourhood for a given problem.
- Use a variety of meta-heuristics to escape local minima.
- Explain how a global constraint propagates in a constraint programming system.