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Bengio, Y., Frejinger, E., Lodi, A., Patel, R., & Sankaranarayanan, S. (septembre 2020). A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs [Communication écrite]. 17th International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research. (CPAIOR 2020), Vienna, Austria. Lien externe
Frejinger, E., Trépanier, M., Amiel, M., Charbonneau, M., Bastin, F., Larsen, E., & Ryo Morin, L. (mars 2015). Analyse des accès aux terminus intermodaux de l'île de Montréal à partir de traces GPS [Communication écrite]. 50e Congrès de l'Association québécoise des transports, Montréal, Québec. Lien externe
Frejinger, E., Morin, L. R., Bastin, F., Larsen, E., Trépanier, M., & Morency, C. (2014). Analyse de données Otto View : Rapport d'étude. (Rapport technique). Non disponible
Larsen, E., Frejinger, E., Gendron, B., & Lodi, A. (2023). Fast Continuous and Integer L-Shaped Heuristics Through Supervised Learning. Informs Journal on Computing, 21 pages. Lien externe
Larsen, E., Lachapelle, S., Bengio, Y., Frejinger, E., Lacoste-Julien, S., & Lodi, A. (2021). Predicting Tactical Solutions to Operational Planning Problems Under Imperfect Information. INFORMS Journal on Computing, 34(1), 227-242. Lien externe
Larsen, E., Lachapelle, S., Bengio, Y., Frejinger, E., Lacoste-Julien, S., & Lodi, A. (2019). Predicting tactical solutions to operational planning problems under imperfect information. (Rapport technique n° DS4DM-2019-003). Lien externe
Morin, L. R., Bastin, F., Frejinger, E., & Trépanier, M. (2019). Modelling Truck Route Choices in an Urban Area Using a Recursive Logit Model and GPS Data. Dans Awasthi, A. (édit.), Sustainable City Logistics Planning: Methods and Applications . Lien externe
Mai, T., Bastin, F., & Frejinger, E. (2018). A decomposition method for estimating recursive logit based route choice models. EURO Journal on Transportation and Logistics, 7(3), 253-275. Lien externe
Mai, T., Frejinger, E., Fosgerau, M., & Bastin, F. (2017). A dynamic programming approach for quickly estimating large network-based MEV models. Transportation Research Part B: Methodological, 98, 179-197. Lien externe
Morin, L. R., Bastian, F., Frejinger, E., & Trépanier, M. (janvier 2017). A GPS-based recursive logit model for truck route choice in urban area [Communication écrite]. TRB 96th Annual Meeting Compendium of Papers, Washington DC, United States (11 pages). Lien externe
Mai, T., Bastin, F., & Frejinger, E. (2017). On the similarities between random regret minimization and mother logit: The case of recursive route choice models. Journal of Choice Modelling, 23, 21-33. Lien externe
Zimmermann, M., Mai, T., & Frejinger, E. (2017). Bike route choice modeling using GPS data without choice sets of paths. Transportation Research Part C: Emerging Technologies, 75, 183-196. Lien externe
Zimmermann, M., Mai, T., & Frejinger, E. (2016). Bike route choice modeling using GPS data without choice sets of paths. (Rapport technique n° CIRRELT-2016-49). Lien externe
