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Sébastien Le DigabelDépartement de mathématiques et de génie industriel
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Audet, C., Hallé-Hannan, E., & Le Digabel, S. (2023). A General Mathematical Framework for Constrained Mixed-variable Blackbox Optimization Problems with Meta and Categorical Variables. Operations Research Forum, 4(1), 37 pages. Lien externe
Audet, C., Le Digabel, S., Rochon Montplaisir, V., & Tribes, C. (2022). Algorithm 1027: NOMAD Version 4: Nonlinear Optimization with the MADS Algorithm. ACM Transactions on Mathematical Software, 48(3), 1-22. Lien externe
Audet, C., Le Digabel, S., Salomon, L., & Tribes, C. (juin 2022). Constrained blackbox optimization with the NOMAD solver on the COCO constrained test suite [Communication écrite]. Genetic and Evolutionary Computation Conference Companion (GECCO 2022), Boston, Massachusetts, USA. Lien externe
Alarie, S., Audet, C., Jacquot, P., & Le Digabel, S. (2022). Hierarchically constrained blackbox optimization. Operations Research Letters, 50(4), 446-451. Lien externe
Audet, C., Le Digabel, S., & Saltet, R. (2022). Quantifying uncertainty with ensembles of surrogates for blackbox optimization. Computational Optimization and Applications, 83(1), 29-66. 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
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
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
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). Lien externe
Audet, C., Le Digabel, S., & Tribes, C. (2019). The mesh adaptive direct search algorithm for granular and discrete variables. SIAM Journal on Optimization, 29(2), 1164-1189. Lien externe
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., 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
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
Al-Maskari, S., Bélisle, E., Li, X., Le Digabel, S., Nawahda, A., & Zhong, J. (avril 2016). Classification with quantification for air quality monitoring [Communication écrite]. 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2016), Auckland, New Zealand. Lien externe
Audet, C., Le Digabel, S., & Tribes, C. (2016). Dynamic scaling in the mesh adaptive direct search algorithm for blackbox optimization. Optimization and Engineering, 17(2), 333-358. Lien externe
Amaioua, N., Le Digabel, S., Audet, C., & Conn, A. R. (juin 2016). Efficient solution of quadratically constrained quadratic subproblems within a direct-search algorithm [Affiche]. Workshop on Nonlinear Optimization Algorithms and Industrial Applications, Toronto, Ontario. Non disponible
Audet, C., Le Digabel, S., & Peyrega, M. (2015). Linear equalities in blackbox optimization. Computational Optimization and Applications, 61(1), 1-23. Lien externe
Audet, C., Ianni, A., Le Digabel, S., & Tribes, C. (2014). Reducing the number of function evaluations in mesh adaptive direct search algorithms. SIAM Journal on Optimization, 24(2), 621-642. Lien externe
Audet, C., Le Digabel, S., Diest, K., Sweatlock, L. A., & Marthaler, D. E. (2013). Metamaterial design by mesh adaptive direct search. Dans Numerical methods for metamaterial design (Vol. 127, p. 71-96). Lien externe
Alarie, S., Audet, C., Garnier, V., Le Digabel, S., & Leclaire, L.-A. (2013). Snow Water Equivalent Estimation Using Blackbox Optimization. Pacific Journal of Optimization, 9(1), 1-21. Lien externe
Audet, C., & Le Digabel, S. (2012). The Mesh Adaptive Direct Search Algorithm for Periodic Variables. Pacific Journal of Optimization, 8(1), 103-119. Lien externe
Audet, C., Dennis, J. E. J., & Le Digabel, S. (2012). Trade-Off Studies in Blackbox Optimization. Optimization Methods & Software, 27(4-5), 613-624. Lien externe
Audet, C., Dennis Jr., J. E., & Le Digabel, S. (2010). Globalization strategies for mesh adaptive direct search. Computational Optimization and Applications, 46(2), 193-215. Lien externe
Abramson, M. A., Audet, C., Dennis Jr., J. E., & Le Digabel, S. (2009). Orthomads: A deterministic MADS instance with orthogonal direct ions. SIAM Journal on Optimization, 20(2), 948-966. Lien externe
Audet, C., Bechard, V., & Le Digabel, S. (2008). Nonsmooth Optimization Through Mesh Adaptive Direct Search and Variable Neighborhood Search. Journal of Global Optimization, 41(2), 299-318. Lien externe
Audet, C., Dennis, J. E., & Le Digabel, S. (2008). Parallel space decomposition of the mesh adaptive direct search algorithm. SIAM Journal on Optimization, 19(3), 1150-1170. Lien externe
Audet, C., Hansen, P., & Le Digabel, S. (2004). Exact solution of three nonconvex quadratic programming problems. Dans Frontiers in global optimization (Vol. 74, p. 25-43). Lien externe
Audet, C., Brimberg, J., Hansen, P., Le Digabel, S., & Mladenovic, N. (2004). Pooling Problem: Alternate Formulations and Solution Methods. Management Science, 50(6), 761-776. Lien externe
Bigeon, J., Le Digabel, S., & Salomon, L. (2024). Handling of constraints in multiobjective blackbox optimization. Computational Optimization and Applications, 45 pages. Lien externe
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
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
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
Bingane, C., Anjos, M. F., & Le Digabel, S. (2019). Tight-and-Cheap Conic Relaxation for the Optimal Reactive Power Dispatch Problem. IEEE Transactions on Power Systems, 34(6), 4684-4693. 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
Bélisle, F., Saunier, N., Bilodeau, G.-A., & Le Digabel, S. (janvier 2017). Optimized Video Tracking for Automated Vehicle Turning Movement Counts [Communication écrite]. 96th Annual Meeting of the Transportation Research Board, Washington, D.C.. Lien externe
Bélisle, F., Saunier, N., Bilodeau, G.-A., & Le Digabel, S. (2017). Optimized video tracking for automated vehicle turning movement counts. Transportation Research Record, 2645(2645), 104-112. Lien externe
Belisle, E., Huang, Z., Le Digabel, S., & Gheribi, A. E. (2015). Evaluation of machine learning interpolation techniques for prediction of physical properties. Computational Materials Science, 98(1), 170-177. Lien externe
Bhattacharya, N., El-Mahi, O., Duclos, E., Beltrame, G., Antoniol, G., Le Digabel, S., & Guéhéneuc, Y.-G. (septembre 2012). Optimizing threads schedule alignments to expose the interference bug pattern [Communication écrite]. 4th International Symposium on Search Based Software Engineering (SSBSE 2012), Riva del Garda, Italy. Lien externe
Conn, A. R., & Le Digabel, S. (2013). Use of quadratic models with mesh-adaptive direct search for constrained black box optimization. Optimization Methods and Software, 28(1), 139-158. Lien externe
Dzahini, K. J., Kokkolaras, M., & Le Digabel, S. (2022). Constrained stochastic blackbox optimization using a progressive barrier and probabilistic estimates. Mathematical Programming, 198(1), 675-732. Lien externe
Dzahini, K. J., Kokkolaras, M., & Le Digabel, S. (2020). Constrained stochastic blackbox optimization using a progressive barrier and probabilistic estimates. (Rapport technique n° G-2020-60). Lien externe
de Souza Dutra, M. D., Anjos, M. F., & Le Digabel, S. (septembre 2019). A Framework for Peak Shaving Through the Coordination of Smart Homes [Communication écrite]. IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT 2019 - Latin America), Gramado, Brazil (6 pages). Lien externe
de Souza Dutra, M. D., Anjos, M. F., & Le Digabel, S. (2019). A general framework for customized transition to smart homes. Energy, 189, 11 pages. Lien externe
de Sousa, V. J. R., Anjos, M. F., & Le Digabel, S. (2019). Improving the linear relaxation of maximum k-cut with semidefinite-based constraints. EURO Journal on Computational Optimization, 7(2), 123-151. Lien externe
de Souza Dutra, M. D., Anjos, M. F., & Le Digabel, S. (2019). A realistic energy optimization model for smart-home appliances. International Journal of Energy Research, 43(8), 3237-3262. Lien externe
De Sousa, V. J. R., Anjos, M. F., & Le Digabel, S. (2016). Computational study of valid inequalities for the maximum k-cut problem. (Rapport technique n° G-2016-17). Lien externe
Duclos, E., Le Digabel, S., Guéhéneuc, Y.-G., & Adams, B. (mars 2013). ACRE: An automated aspect creator for testing C++ applications [Communication écrite]. 17th European Conference on Software Maintenance and Reengineering (CSMR 2013), Genova, Italy. Lien externe
Gheribi, A. E., Pelton, A., Bélisle, 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
Gauthier, L., Saunier, N., Le Digabel, S., & Cao, G. (janvier 2016). Calibration of driving behavior models using derivative-free optimization and video data for montreal highways [Communication écrite]. 95th Annual Meeting of the Transportation Research Board, Washington, DC. Lien externe
Gramacy, R. B., Gray, G. A., Le Digabel, S., Lee, H. K. H., Ranjan, P., Wells, G., & Wild, S. M. (2016). Modeling an augmented lagrangian for blackbox constrained optimization. Technometrics, 58(1), 1-11. Lien externe
Gramacy, R. B., Gray, G. A., Le Digabel, S., Lee, H. K. H., Rajan, P., Wells, G., & Wild, S. M. (2016). Rejoinder. Technometrics, 58(1), 26-29. Lien externe
Gheribi, A. E., Harvey, J.-P., Belisle, E., Robelin, C., Chartrand, P., Pelton, A., Bale, C. W., & Le Digabel, S. (2016). Use of a biobjective direct search algorithm in the process design of material science applications. Optimization and Engineering, 17(1), 27-45. Lien externe
Gramacy, R. B., & Le Digabel, S. (2015). The mesh adaptive direct search algorithm with treed gaussian process surrogates. Pacific Journal of Optimization, 11(3), 419-447. Lien externe
Gertz, E., Hiekkalinna, T., Le Digabel, S., Audet, C., Terwilliger, J. D., & Schäffer, A. A. (2014). PSEUDOMARKER 2.0: efficient computation of likelihoods using NOMAD. BMC Bioinformatics, 15(1). Disponible
Gheribi, A. E., Le Digabel, S., Audet, C., & Chartrand, P. (2013). Identifying optimal conditions for magnesium based alloy design using the Mesh Adaptive Direct Search algorithm. Thermochimica Acta, 559, 107-110. Lien externe
Gheribi, A. E., Audet, C., Le Digabel, S., Belisle, E., Bale, C. W., & Pelton, A. (2012). Calculating Optimal Conditions for Alloy and Process Design Using Thermodynamic and Property Databases, the Fact Sage Software and the Mesh Adaptive Direct Search Algorithm. Calphad-Computer Coupling of Phase Diagrams and Thermochemistry, 36, 135-143. Lien externe
Gheribi, A. E., Robelin, C., Le Digabel, S., Audet, C., & Pelton, A. (2011). Calculating all local minima on liquidus surfaces using the FactSage software and databases and the Mesh Adaptive Direct Search algorithm. Journal of Chemical Thermodynamics, 43(9), 1323-1330. Lien externe
Le Digabel, S., & Wild, S. M. (2023). A taxonomy of constraints in black-box simulation-based optimization. Optimization and Engineering, 2023, 19 pages. Lien externe
Lakhmiri, D., & Le Digabel, S. (2022). Use of Static Surrogates in Hyperparameter Optimization. Operations Research Forum, 3(1). Lien externe
Lakhmiri, D., Alimo, R., & Le Digabel, S. (2022). Anomaly detection for data accountability of Mars telemetry data. Expert Systems With Applications, 189, 116060. 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
Lakhmiri, D., & Le Digabel, S. (2021). Use of static surrogates in hyperparameter optimization. (Rapport technique n° G-2021-10). Lien externe
Lakhmiri, D., Alimo, R., & Le Digabel, S. (2020). Tuning a variational autoencoder for data accountability problem in the Mars Science Laboratory ground data system. (Rapport technique n° 2020-31). Lien externe
Le Digabel, S. (2011). Algorithm 909: NOMAD: Nonlinear optimization with the MADS algorithm. ACM Transactions on Mathematical Software, 37(4), 1-15. Lien externe
Le Digabel, S. (2008). Extensions à l'algorithme de recherche directe mads pour l'optimisation non lisse [Thèse de doctorat, École Polytechnique de Montréal]. Disponible
Le Digabel, S. (2002). Topologie et routage dans les réseaux de communications [Mémoire de maîtrise, École Polytechnique de Montréal]. Lien externe
Minville, M., Cartier, D., Guay, C., Leclaire, L.-A., Audet, C., Le Digabel, S., & Merleau, J. (2014). Improving process representation in conceptual hydrological model calibration using climate simulations. Water Resources Research, 50(6), 5044-5073. Lien externe
Picheny, V., Gramacy, R. B., Wild, S., & Le Digabel, S. (décembre 2016). Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian [Communication écrite]. 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain. Lien externe
Pourbagian, M., Talgorn, B., Habashi, W. G., Kokkolaras, M., & Le Digabel, S. (2015). Constrained problem formulations for power optimization of aircraft electro-thermal anti-icing systems. Optimization and Engineering, 16(4), 663-693. Lien externe
Perron, S., Hansen, P., Le Digabel, S., & Mladenovic, N. (2010). Exact and heuristic solutions of the global supply chain problem with transfer pricing. European Journal of Operational Research, 202(3), 864-879. Lien externe
Rodrigues de Sousa, V. J., 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
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
Talgorn, B., Le Digabel, S., & Kokkolaras, M. (2015). Statistical Surrogate Formulations for Simulation-Based Design Optimization. Journal of Mechanical Design, 137(2), 021405. Lien externe
Talgorn, B., Le Digabel, S., & Kokkolaras, M. (août 2014). Problem Formulations for Simulation-Based Design Optimization Using Statistical Surrogates and Direct Search [Communication écrite]. ASME 2014 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE 2014), Buffalo, New York. Lien externe
