| Stochastic short-term hydropower planning with inflow scenario trees S Séguin, SE Fleten, P Côté, A Pichler, C Audet European Journal of Operational Research 259 (3), 1156-1168, 2017 | 89 | 2017 |
| Self-scheduling short-term unit commitment and loading problem S Séguin, P Côté, C Audet IEEE Transactions on Power Systems 31 (1), 133-142, 2015 | 64 | 2015 |
| An optimization model to maximize energy generation in short-term hydropower unit commitment using efficiency points M Daadaa, S Séguin, K Demeester, MF Anjos International Journal of Electrical Power & Energy Systems 125, 106419, 2021 | 43 | 2021 |
| Robotic process automation (RPA) using an integer linear programming formulation S Séguin, I Benkalai Cybernetics and systems 51 (4), 357-369, 2020 | 27 | 2020 |
| Scenario-tree modeling for stochastic short-term hydropower operations planning S Séguin, C Audet, P Côté Journal of Water Resources Planning and Management 143 (12), 04017073, 2017 | 27 | 2017 |
| Minimizing the number of robots required for a Robotic Process Automation (RPA) problem S Séguin, H Tremblay, I Benkalaï, DE Perron-Chouinard, X Lebeuf Procedia Computer Science 192, 2689-2698, 2021 | 17 | 2021 |
| Improving patient transportation in hospitals using a mixed-integer programming model S Séguin, Y Villeneuve, CH Blouin-Delisle Operations Research for Health Care 23, 100202, 2019 | 14 | 2019 |
| Ai-based scheduling models, optimization, and prediction for hydropower generation: Opportunities, issues, and future directions Y Villeneuve, S Séguin, A Chehri Energies 16 (8), 3335, 2023 | 13 | 2023 |
| Computing a lower bound for the solution of a Robotic Process Automation (RPA) problem using network flows I Benkalaï, S Séguin, H Tremblay, G Glangine 2020 7th International Conference on Control, Decision and Information …, 2020 | 4 | 2020 |
| Quantifying the Impact of Scenario Tree Generation Methods on the Solution of the Short-term Hydroscheduling Problem M Daadaa, S Séguin, MF Anjos, K Demeester GERAD, HÉC Montréal, 2022 | 3 | 2022 |
| Optimisation stochastique de la répartition spatio-temporelle d'un volume d'eau aux groupes turbo-alternateurs d'un système de production hydroélectrique S Séguin Ecole Polytechnique, Montreal (Canada), 2016 | 3 | 2016 |
| A survey on AI-based scheduling models, optimization and prediction for hydropower generation: Variants, chal-lenges, and future directions Y Villeneuve, S Séguin, A Chehri Les Cahiers du GERAD ISSN 711, 2440, 2022 | 2 | 2022 |
| Scenario tree modeling for stochastic short-term hydropower operations planning S Séguin, P Côté, C Audet GERAD, 2016 | 2 | 2016 |
| Quantifying the impact of scenario tree generation and reduction methods on the solution of the short-term hydroscheduling problem M Daadaa, S Séguin, MF Anjos, K Demeester Energy Systems, 1-30, 2023 | 1 | 2023 |
| Short-term hydropower optimization in the day-ahead market using a nonlinear stochastic programming model M Jafari Aminabadi, S Séguin, I Fofana, SE Fleten, EK Aasgård Energy Systems, 1-25, 2023 | 1 | 2023 |
| Robotic Process Automation (RPA) using a heuristic method and the effective resistance of a graph H Tremblay, S Séguin, LA Boily, V Du Paul, S Lalancette Procedia Computer Science 225, 3388-3394, 2023 | 1 | 2023 |
| A fast solution approach to solve the generator maintenance scheduling and hydropower production problems simultaneously G Glangine, S Seguin, K Demeester Procedia Computer Science 207, 3808-3817, 2022 | 1 | 2022 |
| Hydropower optimization S Séguin Les Cahiers du GERAD ISSN 711, 2440, 2020 | 1 | 2020 |
| Short-term unit commitment and loading problem S Séguin, P Côté, C Audet GERAD, 2014 | 1 | 2014 |
| Hybrid Genetic Algorithms and Heuristics for Nonlinear Short-Term Hydropower Optimization: A Comparative Analysis MJ Aminabadi, S Séguin, I Fofana Procedia Computer Science 246, 282-291, 2024 | | 2024 |
Pascal CôtéIngénieur analyste en recherche opérationnelle, Rio Tinto Alcan Énergie électriqueVerified email at riotinto.com
