- When: 11th October 2016 14:00 - 15:00
- Where: Cole 1.33
- Series: School Seminar Series
- Format: Seminar
Evolutionary algorithms (EA) has developed as an academic discipline since the 1960s. The subject has spawned major subfields such as swarm intelligence and genetic programming and is applied to a wide variety of practical real world problems in science medicine and engineering. EAs are often the only practical method of solving large combinatorial optimisation problems and have achieved best-known results on a variety of benchmark problems. The global academic EA community is highly active, supporting several large international conferences and high-quality international journals. Despite this activity, sustained over decades, the community has struggled to make significant progress on developing a satisfactory theory of EAs. At the same time, substantial progress has been made on developing more sophisticated EAs that are ever more powerful but ever less amenable to theoretical study. In this talk I will outline some of the main approaches to a theory of EAs and illustrate the gap between those EAs that can be theoretically analysed by those approaches and EAs that are being used in practice. I will conclude with some interesting current developments and key open questions.
John McCall is a Professor of Computing Science at Robert Gordon University. He works in the Computational Intelligence research group, which he founded in 2003. He has over twenty years research experience in naturally-inspired computing. His research focuses on the study and analysis of a range of naturally-inspired optimization algorithms (genetic algorithms, particle swarm optimisation, ant colony optimisation, estimation of distribution algorithms etc.) and their application to difficult learning and optimisation problems, particularly real-world problems arising in complex engineering and medical / biological systems. Application areas of this research include medical decision support, data modeling of drilling operations, analysis of biological sequences, staff rostering and scheduling, industrial process optimization and bio-control. He has over 90 publications in books, journals and conferences. He has successfully supervised 13 PhD students and has examined over 15 PhD theses.