The MALEO (Machine Learning and Optimisation) group had a strong presence with two full papers, a poster, and a tutorial at this year’s Genetic and Evolutionary Computation Conference (GECCO) 2026 in San Jose, Costa Rica.
The highlight of the conference was the paper “Exploration of Pareto-preserving Search-Space Transformations in Multi-Objective Test Functions” by Diederick Vermetten (LIP6, Sorbonne University) and Jeroen Rook which won the Best Paper Award in the BBSR track. In this work, they propose two transformations that can be combined with any existing test problem, allowing for better benchmarking of multi-objective algorithms.
In addition, the group presented:
“Digging to the Ground Truth: Solving Multi-objective Gray-Box Optimization Problems through Hyperplane Elimination” as a full paper, in collaboration with Francisco Chicano (ITIS Software, University of Malaga) and Darrell Whitley (Colorado State University) “Multi-Objective Pipeline Optimisation and Configuration of Automatic Train Operation Trajectories” as a poster, in collaboration with the LDM group of the Mechanical Engineering Faculty. “Advanced Use of Automatic Algorithm Configuration: Single- and Multi-Objective Approaches” as a tutorial together with Manuel López-Ibáñez (University of Manchester) Overall, the MALEO research group had a great time at the flagship conference on evolutionary computation and enjoyed the many inspiring contributions presented there. They are also grateful that their work is recognised, which is reflected in the number of accepted papers, but also honoured with a best paper award for two years in a row.
