Items where Author is "Côté, Pascal"
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A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
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Author
Edom, É., Anjos, M. F., D'Ambrosio, C., van Ackooij, W., Côté, P., & Séguin, S. (2020). On the impact of the power production function approximation on hydropower maintenance scheduling. (Technical Report n° G-2020-22). External link
Audet, C., Côté, P., Poissant, C., & Tribes, C. (2020). Monotonic grey box direct search optimization. Optimization Letters, 14(1), 3-18. External link
Rodriguez, J. A., Anjos, M. F., Côté, P., & Desaulniers, G. (2020). Accelerating Benders decomposition for short-term hydropower maintenance scheduling. European Journal of Operational Research, 289(1), 240-253. External link
Audet, C., Côté, P., Poissant, C., & Tribes, C. (2019). Monotonic grey box optimization. (Technical Report n° G-2019-15). External link
Rodríguez Sarasty, J. A., Anjos, M. F., Côté, P., & Desaulniers, G. (2018). Stochastic hydropower generator maintenance scheduling via Benders decomposition. (Technical Report n° G-2018-32). External link
Rodríguez Sarasty, J. A., Anjos, M. F., Côté, P., & Desaulniers, G. (2017). MILP formulations for generator maintenance scheduling in hydropower systems. (Technical Report n° G-2017-63). External link
Séguin, S., Fleten, S.-E., Côté, P., Pichler, A., & Audet, C. (2017). Stochastic short-term hydropower planning with inflow scenario trees. European Journal of Operational Research, 259(3), 1156-1168. External link
Séguin, S., Audet, C., & Côté, P. (2017). Scenario-tree modeling for stochastic short-term hydropower operations planning. Journal of Water Resources Planning and Management, 143(12), 12 pages. External link
Côté, P., Demeester, K., Orban, D., & Towhidi, M. (2017). Numerical methods for stochastic dynamic programming with application to hydropower optimization. (Technical Report n° G-2017-64). External link
Séguin, S., Audet, C., & Côté, P. (2016). Scenario tree modeling for stochastic short-term hydropower operations planning. (Technical Report n° G-2016-54). External link
Séguin, S., Fleten, S.-E., Côté, P., Pichler, A., & Audet, C. (2016). Stochastic short-term hydropower planning with inflow scenario trees. (Technical Report n° G-2015-97). External link
Séguin, S., Côté, P., & Audet, C. (2016). Self-Scheduling Short-Term Unit Commitment and Loading Problem. IEEE Transactions on Power Systems, 31(1), 133-142. External link
Rodríguez, J. A., Anjos, M. F., Audet, C., & Côté, P. (2016, June). A decomposition approach for the hydropower operation and maintenance scheduling [Poster]. Workshop on Nonlinear Optimization Algorithms and Industrial Applications, Toronto, Ontario. Unavailable
Séguin, S., Côté, P., & Audet, C. (2014). Short-term unit commitment and loading problem. (Technical Report n° G-2014-21). External link
Côté, P. (2010). Gestion d'un ensemble d'installations hydroélectriques soumis à une contrainte de demande [Ph.D. thesis, École Polytechnique de Montréal]. Available
Research Director
Demeester, K. (2017). Méthodes numériques appliquées à la programmation dynamique stochastique pour la gestion d'un système hydroélectrique [Master's thesis, École Polytechnique de Montréal]. Available
Séguin, S. (2016). Optimisation stochastique de la répartition spatio-temporelle d'un volume d'eau aux groupes turbo-alternateurs d'un système de production hydroélectrique [Ph.D. thesis, École Polytechnique de Montréal]. Available