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Amaioua, N., Audet, C., Conn, A. R., & Le Digabel, S. (2018). Efficient solution of quadratically constrained quadratic subproblems within the mesh adaptive direct search algorithm. European Journal of Operational Research, 268(1), 13-24. Lien externe
Audet, C., Conn, A. R., Le Digabel, S., & Peyrega, M. (2018). A progressive barrier derivative-free trust-region algorithm for constrained optimization. Computational Optimization and Applications, 71(2), 307-329. Lien externe
Audet, C., Ihaddadene, A., Le Digabel, S., & Tribes, C. (2018). Robust optimization of noisy blackbox problems using the Mesh Adaptive Direct Search algorithm. Optimization Letters, 12(4), 675-689. Lien externe
Audet, C., Kokkolaras, M., Le Digabel, S., & Talgorn, B. (2018). Order-based error for managing ensembles of surrogates in mesh adaptive direct search. Journal of Global Optimization, 70(3), 645-675. Lien externe
Bingane, C., Anjos, M. F., & Le Digabel, S. (2018). Tight-and-Cheap Conic Relaxation for the AC Optimal Power Flow Problem. IEEE Transactions on Power Systems, 33(6), 7181-7188. Lien externe
Gheribi, A. E., Pelton, A., Belisle, E., Le Digabel, S., & Harvey, J.-P. (2018). On the prediction of low-cost high entropy alloys using new thermodynamic multi-objective criteria. ACTA Materialia, 161, 73-82. Lien externe
Rodrigues de Sousa, V. J., Anjos, M. F., & Le Digabel, S. (2018). Computational study of valid inequalities for the maximum k-cut problem. Annals of Operations Research, 265(1), 5-27. Lien externe
Talgorn, B., Audet, C., Le Digabel, S., & Kokkolaras, M. (2018). Locally weighted regression models for surrogate-assisted design optimization. Optimization and Engineering, 19(1), 213-238. Lien externe
