For an exhaustive list, please refer to my Google scholar profile.
F. Pacaud, S. Shin, A. Montoison, M. Schanen, M. Anitescu. Condensed-space methods for nonlinear programming on GPUs. 2024. arXiv
Y. Kim, F. Pacaud, K. Kim, M. Anitescu. Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition. 2021. arXiv
S. Shin, F. Pacaud, M. Anitescu. Accelerating optimal power flow with GPUs: SIMD abstraction of nonlinear programs and condensed-space interior-point methods Electric Power Systems Research (EPSR). 2024. URL, arXiv
F. Pacaud, M. Schanen, S. Shin, D.A. Maldonado, M. Anitescu. Parallel Interior-Point Solver for Block-Structured Nonlinear Programs on SIMD/GPU Architectures. Optimization Methods and Software (OMS). 2024. URL. arXiv
F. Pacaud, D. A. Maldonado, S. Shin, M. Schanen, and M. Anitescu. A feasible reduced space method for real-time optimal power flow. Electric Power Systems Research (EPSR). 2022. URL arXiv
F. Pacaud, S. Shin, D.A. Maldonado, M. Schanen, M. Anitescu. Accelerating condensed interior-point methods on SIMD/GPU architectures. Journal of Optimization Theory and Applications (JOTA). 2022. URL. arXiv
F. Pacaud, M. De Lara, J.P. Chancelier, P. Carpentier. Distributed Multistage Stochastic Optimization of Large-Scale Microgrids under Stochasticity. IEEE Transactions on Power Systems. 2021. URL. arXiv
P. Carpentier, J.P. Chancelier, M. De Lara, F. Pacaud. Mixed Spatial and Temporal Decompositions for Large-Scale Multistage Stochastic Optimization Problems. Journal of Optimization Theory and Applications (JOTA). 2020. URL. arXiv
V. Leclere, P. Carpentier, J.P. Chancelier, A. Lenoir and F. Pacaud. Exact converging bounds for Stochastic Dual Dynamic Programming via Fenchel duality. SIAM Journal on Optimization (SIOPT). 2020. URL. HAL
P. Carpentier, J.P. Chancelier, V. Leclere and F.Pacaud. Stochastic decomposition applied to large-scale hydro valleys management. European Journal of Operation Research (EJOR). 2018. URL. arXiv
F. Pacaud, S. Shin. GPU-accelerated dynamic nonlinear optimization with ExaModels and MadNLP. Accepted in the proceedings of the 63th Conference on Decision and Control (CDC). 2024. arXiv
S. Shin, F. Pacaud, E. Contantinescu, M. Anitescu Constrained Policy Optimization for Stochastic Optimal Control under Nonstationary Uncertainties. American Control Conference (ACC), 2023.
D. Cole, S. Shin, F. Pacaud, VM. Zavala, M. Anitescu Exploiting GPU/SIMD Architectures for Solving Linear-Quadratic MPC Problems. American Control Conference (ACC), 2023.
F. Pacaud, M. Schanen, DA. Maldonado, A. Montoison, V. Churavy, J. Samaroo, M. Anitescu. Batched second-order adjoint sensitivity for reduced space methods. SIAM Conference on Parallel Processing for Scientific Computing (SIAM-PP). 2022. URL
M. Anitescu, K. Kim, Y. Kim, A. Maldonado, F. Pacaud, V. Rao, M. Schanen, S. Shin, and A. Subramanian. Targeting Exascale with Julia on GPUs for multiperiod optimization with scenario constraints. SIAG/OPT Views and News, 2021. URL.