Evolutionary algorithms are computer algorithms inspired by biological evolutionary theories. They are commonly used for solving benchmark problems in computer science as well as complex real-world problems. In high energy physics and the related fields these algorithms have been successfully tested and their presence gradually increases. This seminar will review classical evolutionary algorithms such as Genetic Algorithms, Genetic Programming and Evolutionary Strategies, and will introduce new developments in the field such as Gene Expression Programming. Applications of these algorithms for solving high energy physics data analysis problems and computing related tasks such as job scheduling optimisation on computational grids will be reviewed and discussed.
Liliana Teodorescu is a Lecturer at Brunel University, London, UK. She holds a Ph.D. in Particle Physics and has more than 10 years research experience on medium and large scale particle physics experiments. She worked at renown laboratories around the world: Thomas Jefferson National Accelerator Facility (TJNAF), USA, Instituto Nazionale di Fisica Nucleare (INFN) – Pisa, Italy, Stanford Linear Accelerator Centre (SLAC), USA and European Laboratory for Particle Physics (CERN), Geneva. She currently works on CMS (CERN) and BaBar (SLAC) experiments. In addition of physics research in these experiments, she is interested in cross-disciplinary research involving particle physics and various fields of computer science for development of novel data analysis techniques for particle physics.