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Bengio, Y., Frejinger, E., Lodi, A., Patel, R., & Sankaranarayanan, S. (2020, September). A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs [Paper]. 17th International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research. (CPAIOR 2020), Vienna, Austria. External link
Frejinger, E., Trépanier, M., Amiel, M., Charbonneau, M., Bastin, F., Larsen, E., & Ryo Morin, L. (2015, March). Analyse des accès aux terminus intermodaux de l'île de Montréal à partir de traces GPS [Paper]. 50e Congrès de l'Association québécoise des transports, Montréal, Québec. External link
Frejinger, E., Morin, L. R., Bastin, F., Larsen, E., Trépanier, M., & Morency, C. (2014). Analyse de données Otto View : Rapport d'étude. (Technical Report). Unavailable
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. External link
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. External link
Larsen, E., Lachapelle, S., Bengio, Y., Frejinger, E., Lacoste-Julien, S., & Lodi, A. (2019). Predicting tactical solutions to operational planning problems under imperfect information. (Technical Report n° DS4DM-2019-003). External link
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. In Awasthi, A. (ed.), Sustainable City Logistics Planning: Methods and Applications . External link
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. External link
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. External link
Morin, L. R., Bastian, F., Frejinger, E., & Trépanier, M. (2017, January). A GPS-based recursive logit model for truck route choice in urban area [Paper]. TRB 96th Annual Meeting Compendium of Papers, Washington DC, United States (11 pages). External link
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. External link
Sadana, U., Chenreddy, A., Delage, E., Forel, A., Frejinger, E., & Vidal, T. (2024). A survey of contextual optimization methods for decision-making under uncertainty. European Journal of Operational Research, 19 pages. External link
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. External link
Zimmermann, M., Mai, T., & Frejinger, E. (2016). Bike route choice modeling using GPS data without choice sets of paths. (Technical Report n° CIRRELT-2016-49). External link
