Documents publiés en "2021"

Article de revue

Alarie, S., Audet, C., Bouchet, P.-Y., & Le Digabel, S. (2021). Optimization of stochastic blackboxes with adaptive precision. SIAM Journal on Optimization, 31(4), 3127-3156. Lien externe

Alarie, S., Audet, C., Gheribi, A. E., Kokkolaras, M., & Le Digabel, S. (2021). Two decades of blackbox optimization applications. EURO Journal on Computational Optimization, 9, 100011 (13 pages). Disponible

Audet, C., Bigeon, J., Cartier, D., Le Digabel, S., & Salomon, L. (2021). Performance indicators in multiobjective optimization. European Journal of Operational Research, 292(2), 397-422. Lien externe

Audet, C., Dzahini, K. J., Kokkolaras, M., & Le Digabel, S. (2021). Stochastic mesh adaptive direct search for blackbox optimization using probabilistic estimates. Computational Optimization and Applications, 79(1), 1-34. Lien externe

Bigeon, J., Le Digabel, S., & Salomon, L. (2021). DMulti-MADS: mesh adaptive direct multisearch for bound-constrained blackbox multiobjective optimization. Computational Optimization and Applications, 79(2), 301-338. Lien externe

Lakhmiri, D., Le Digabel, S., & Tribes, C. (2021). HyperNOMAD: Hyperparameter Optimization of Deep Neural Networks Using Mesh Adaptive Direct Search. ACM Transactions on Mathematical Software, 47(3), 1-27. Lien externe

Rodrigues de Sousa, V., Anjos, M. F., & Le Digabel, S. (2021). Computational study of a branching algorithm for the maximum k-cut problem. Discrete Optimization, 100656 (20 pages). Lien externe

Rapport technique

Alarie, S., Audet, C., Jacquot, P., & Le Digabel, S. (2021). Hierarchically constrained blackbox optimization. (Rapport technique n° G-2021-65). Lien externe

Audet, C., Le Digabel, S., & Saltet, R. (2021). Quantifying uncertainty with ensembles of surrogates for blackbox optimization. (Rapport technique n° 2021-37). Lien externe

Audet, C., Le Digabel, S., Rochon Montplaisir, V., & Tribes, C. (2021). NOMAD version 4: Nonlinear optimization with the MADS algorithm. (Rapport technique n° G-2021-23). Lien externe

Lakhmiri, D., & Le Digabel, S. (2021). Use of static surrogates in hyperparameter optimization. (Rapport technique n° G-2021-10). Lien externe

Communication écrite

Bingane, C., Anjos, M. F., & Le Digabel, S. (juillet 2021). CONICOPF: conic relaxations for AC optimal power flow computations [Communication écrite]. IEEE Power and Energy Society General Meeting (PESGM 2021), Washington, D.C., USA (5 pages). Lien externe

Bingane, C., Anjos, M. F., & Le Digabel, S. (juillet 2021). Tight-and-cheap conic relaxation for the optimal reactive power dispatch problem [Communication écrite]. 2021 IEEE Power and Energy Society General Meeting (PESGM 2021), Washington, D.C., USA (1 page). Lien externe