Keynote Speaker: Ekhine Irurozki received a Ph.D. in Computer Science from the University of the Basque Country, Spain, in 2014. Since 2020 she has been Assistant Professor at Télécom Paris. Before joining Télécom Paris, she was a postdoc fellow at the Machine Learning Department at the Basque Center for Applied Mathematics (BCAM) in Bilbao from 2017 to 2020. She previously worked from 2015 to 2017 as Postdoctoral Fellow at the Basque Country University. Her main research interest is the development of optimization and artificial intelligence techniques for automatic decision making, with a particular interest in statistical problems with ranked data.Dr. Irurozki has led the cybersecurity lab and has been part of the transfer unit at BCAM, having worked in several projects with companies in the manufacturing and services sectors. She has received the Extraordinary Doctoral Award from the Basque Country University.
Keynote Title: Uniform crossovers for permutations
Keynote Abstract: Crossover and recombination are the two most critical components of evolutionary algorithms. The traditional operators for general problems cannot be directly adapted for problems in which the solution is coded as a permutation. Different alternatives have been proposed, most of which adapt well-known crossovers for multidimensional real data. However, these approaches lack any natural interpretation.
In this talk, we formalize desirable properties for crossovers and describe purely combinatorial crossover and recombination operators for permutation problems. These operators formally define the set of permutations that can be generated in terms of the Cayley and Kedall’s-tau distances. Then, they select one permutation in the set uniformly at random. Both are entirely based on tools from enumerative combinatorics.