NomadBBO: A direct-search framework for constrained mixed-variable blackbox optimization in Python
E. Hallé-Hannan, C. Tribes (2026).
Preprint: arXiv:2609.19333.
Surrogate-based categorical neighborhoods for mixed-variable blackbox optimization
C. Audet, Y. Diouane, E. Hallé-Hannan, S. Le Digabel, C. Tribes (2026).
Preprint: arXiv:2603.27839.
CatMADS: Mesh adaptive direct-search for constrained blackbox optimization with categorical variables
C. Audet, Y. Diouane, E. Hallé-Hannan, S. Le Digabel, C. Tribes (2025).
To appear in SIAM Journal on Optimization (SIOPT). Preprint: arXiv:2506.06937.
A distance for mixed-variable and hierarchical domains with meta variables
E. Hallé-Hannan, C. Audet, Y. Diouane, S. Le Digabel, P. Saves (2025).
Neurocomputing 653, 131208.
DOI: 10.1016/j.neucom.2025.131208
A General Mathematical Framework for Constrained Mixed-variable Blackbox Optimization Problems with Meta and Categorical Variables
C. Audet, E. Hallé-Hannan, S. Le Digabel (2023). Operations Research Forum 4(12).
DOI: 10.1007/s43069-022-00180-6