This project is concerned with developing practical solutions for real-world large-scale optimisation.
Many real-world optimisation problems are large-scale, expensive to evaluate, and difficult to formulate, involving thousands of variables and constraints. Existing optimisation methods are ill-equipped to deal with large-scale problems, although they may perform well on smaller problems.
The project is involved in inter-disciplinary approaches integrating ideas from mathematical programming, meta-heuristics, and operations research. It will continue to build on our research strength in the area of large-scale optimisation using meta-heuristics. Our aim is to develop effective optimisation techniques for solving real-world large-scale optimisation problems that really matter to the practitioners.
The group publishes regularly in the top evolutionary computation journals and conferences, and has been actively involved in IEEE CIS taskforce on large-scale global optimisation, organising special sessions and competitions on this topic for the last few years. It attracts funding from both ARC Discovery and Linkage grants.
- Associate Professor Xiaodong Li (contact person)
- Dr Kai Qin
- Dr Yi Mei
- Mohammad Nabi Omidvar
- Borhan Kazimipour
- Asad Mohammadi
- Mohammad Haqqani