For an exhaustive list, please refer to my Google scholar profile.
A. Pozharskiy, F. Pacaud, M. Diehl, A. Nurkanović. CCOpt: an Open-Source Solver for Large-Scale Mathematical Programs with Complementarity Constraints. arxiv
A. Montoison, F. Pacaud, M. Saunders, S. Shin, D. Orban. MadNCL: a GPU implementation of algorithm NCL for large-scale, degenerate nonlinear programs. 2025. arxiv
F. Pacaud. Sensitivity analysis for parametric nonlinear programming: A tutorial. 2025. arxiv
W. Kuang, A. Montoison, V. Rao, F. Pacaud, M. Anitescu. Recovering sparse DFT from missing signals via interior point method on GPU. 2025. arxiv
F. Pacaud, S. Shin, A. Montoison, M. Schanen, M. Anitescu. Condensed-space methods for nonlinear programming on GPUs. 2024. arXiv
F. Geth, F. Pacaud, Rahmat Heidari. Solving three-phase distribution OPF with nonlinear programming. Electric Power Systems Research (EPSR). 2026. URL
F. Pacaud, A. Nurkanović, A. Pozharskiy, A. Montoison, S. Shin. An Augmented Lagrangian Method on GPU for Security-Constrained AC Optimal Power Flow. Electric Power Systems Research (EPSR). 2026. URL, arxiv
S. Johnson, D. Lauinger, S. Shin, F. Pacaud. ExaModelsPower.jl: A GPU-Compatible Modeling Library for Nonlinear Power System Optimization. Electric Power Systems Research (EPSR). 2026. arxiv
JP. Chancelier, M. De Lara, T. Lindegaard, F. Pacaud, T. Pennanen, AP. Perkkiö. Optimal operation and valuation of electricity storage systems in intraday markets. Computational Management Science. 2026. URL, arxiv
Y. Kim, F. Pacaud, K. Kim, M. Anitescu. Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition. SIAM Journal on Scientific Computing. 2025. URL arxiv
A. Engelmann, S. Shin, F. Pacaud, VM. Zavala Scalable primal decomposition schemes for large-scale infrastructure networks IEEE Transactions on Control of Network Systems. 2025. URL, 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
A. Montoison, F. Pacaud, S. Shin, M. Anitescu. GPU implementation of second-order linear and nonlinear programming solvers. NeurIPS Workshop on GPU-Accelerated and Scalable Optimization, 2025. URL
F. Pacaud, S. Shin. GPU-accelerated dynamic nonlinear optimization with ExaModels and MadNLP. IEEE 63rd Conference on Decision and Control (CDC). 2024. URL 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.