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Keutchayan, J., Munger, D., & Gendreau, M. (2020). On the scenario-tree optimal-value error for stochastic programming problems. Mathematics of Operations Research, 45(4), 1572-1595. Lien externe
Keutchayan, J., Gendreau, M., & Saucier, A. (2017). Quality evaluation of scenario-tree generation methods for solving stochastic programming problems. Computational Management Science, 14(3), 333-365. Lien externe
Keutchayan, J., Munger, D., & Gendreau, M. (2017). On the scenario-tree optimal-value error for stochastic programming problems. (Rapport technique n° CIRRELT-2017-73). Lien externe
Keutchayan, J., Munger, D., & Gendreau, M. (2017). On the scenario-tree optimal-value error for stochastic programming problems. (Rapport technique n° CIRRELT-2017-05). Lien externe
Keutchayan, J., Munger, D., Gendreau, M., & Bastin, F. (2017). A new scenario-tree generation approach for multistage stochastic programming problems based on a demerit criterion. (Rapport technique n° CIRRELT-2017-74). Lien externe
Keutchayan, J., Munger, D., & Gendreau, M. (2017). On the Scenario-Tree Optimal-Value Error for Stochastic Programming Problems. (Rapport technique n° CIRRELT-2016-05). Lien externe
Keutchayan, J., Gendreau, M., & Saucier, A. (2017). Quality evaluation of scenario-tree generation methods for solving stochastic programming problem. (Rapport technique n° CIRRELT-2017-17). Lien externe
Keutchayan, J., Gendreau, M., & Saucier, A. (2016). Quality Evaluation of Scenario-Tree Generation Methods for Solving High-Dimensional Stochastic Programs. (Rapport technique n° CIRRELT-2016-46). Non disponible
Keutchayan, J. (2018). Approximation d'espérances conditionnelles guidée par le problème en optimisation stochastique multi-étapes [Thèse de doctorat, École Polytechnique de Montréal]. Disponible