Documents publiés en "2026"

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Daadaa, M., Séguin, S., Anjos, M. F., & Demeester, K. (2026). Optimizing strategies for short-term hydropower scheduling using a blackbox optimization framework. Engineering Optimization, 23 pages. Lien externe

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Liu, H., Wang, S., Botterud, A., & Anjos, M. F. (2026). Stochastic capacity accreditation: Incentivizing resource adequacy under weather uncertainty. (Rapport technique n° G-2026-36). Lien externe

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Rodrigues, B., Carvalho, M., Anjos, M. F., & Sugishita, N. (2026). Unboundedness in Bilevel Optimization. Mathematical Programming, 37 pages. Lien externe

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Stuart Leslie, D., Anjos, M. F., Anosova, O. D., Bearon, R., Calder A., M., Carrillo, J. A., Champneys, A., Coates, T., Cohen, S., Enright, J. A., Etheridge, A. M., Higham, D. J., Jaggi, S., Kurlin, V. A., Robert, L., Rajpaul, V., Marr, C., Nemeth, C., Nicolau, D. V., ... Yu, Y. (2026). Mathematics in the age of artificial intelligence: A primer on key topics in the mathematical sciences that underpin AI. (Rapport technique). Lien externe

Şuvak, Z., Anjos, M. F., Brotcorne, L., & Cattaruzza, D. (2026). Design of Poisoning Attacks on Linear Regression Using Bilevel Optimization. Dans Dang, S., Deza, A., Gupta, S., McNicholas, P. D., Pokutta, S., & Sugiyama, M. (édit.), Data Science and Optimization (Vol. 91, p. 41-65). Lien externe

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Villeneuve, Y., Séguin, S., Anjos, M. F., & Demeester, K. (2026). Managing short-term hydropower production with a multi-agent reinforcement learning model. (Rapport technique n° G-2026-37). Lien externe

Villeneuve, Y., Séguin, S., Demeester, K., & Anjos, M. F. (juin 2026). A Multi-Agent Reinforcement Learning Approach to Short-Term Hydropower Scheduling [Communication écrite]. 22nd International Conference on the European Energy Market (EEM 2026), Trondheim, Norway (6 pages). Lien externe

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Weldeyesus, A. G., & Anjos, M. F. (2026). IPNSDP: A solver for nonlinear semidefinite programming with automatic differentiation and chordal decomposition. (Rapport technique n° G-2026-06). Lien externe

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Zhang, L., Anjos, M. F., & Chalmers, H. (2026). A stochastic programming model for planning CO₂ transport infrastructure with uncertainty. Computational Management Science, 23(1), 28 pages. Lien externe