Evolutionary computing and optimisation
Optimisation is the search for better, more efficient solutions to benchmark and real-world problems. The optimisation research group focusses on developing new algorithms for discovering these solutions, based on the latest artificial intelligence research.
Our work is focussed on evolutionary algorithms, genetic programming, hyperheuristics, swarm intelligence and multi- and many- objective versions of these.
Particular research topics include new algorithm development, optimisation under uncertainty, interactive evolution and the use of surrogates in optimisation.
Group members
- Key contact: Professor Ed Keedwell - Professor of Artificial Intelligence (Research Lead)
- Professor Richard Everson - Professor of Machine Learning
- Professor Jonathan Fieldsend - Professor in Computational Intelligence
- Dr Ke Li - Senior Lecturer
- Dr Alberto Moraglio - Senior Lecturer
- Neil Vaughan - Associate Professor
- David Walker - Senior Lecturer
- Khulood Alyahya - Lecturer
- Tinkle Chugh - Lecturer
Research projects
For a full list of current and recent research projects within this strand of our work, please see our research projects page.
