| Pyomo-optimization modeling in python WE Hart, CD Laird, JP Watson, DL Woodruff, GA Hackebeil, BL Nicholson, ... Springer 67, 277, 2017 | 1653 | 2017 |
| Pyomo-optimization modeling in python ML Bynum, GA Hackebeil, WE Hart, CD Laird, BL Nicholson, JD Siirola, ... Springer 67 (s 32), 2021 | 934 | 2021 |
| pyomo.dae: a modeling and automatic discretization framework for optimization with differential and algebraic equations B Nicholson, JD Siirola, JP Watson, VM Zavala, LT Biegler Mathematical Programming Computation 10 (2), 187-223, 2018 | 147 | 2018 |
| Scripting custom workflows ML Bynum, GA Hackebeil, WE Hart, CD Laird, BL Nicholson, JD Siirola, ... Pyomo—Optimization modeling in python, 67-81, 2021 | 119 | 2021 |
| On-line state estimation of nonlinear dynamic systems with gross errors B Nicholson, R Lopez-Negrete, LT Biegler Computers & chemical engineering 70, 149-159, 2014 | 63 | 2014 |
| Next generation multi-scale process systems engineering framework DC Miller, JD Siirola, D Agarwal, AP Burgard, A Lee, JC Eslick, ... Computer Aided Chemical Engineering 44, 2209-2214, 2018 | 43 | 2018 |
| Benchmarking ADMM in nonconvex NLPs JS Rodriguez, B Nicholson, C Laird, VM Zavala Computers & Chemical Engineering 119, 315-325, 2018 | 36 | 2018 |
| Sensor placement optimization using Chama KA Klise, BL Nicholson, CD Laird Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2017 | 30 | 2017 |
| Scalable parallel nonlinear optimization with pynumero and parapint JS Rodriguez, RB Parker, CD Laird, BL Nicholson, JD Siirola, ML Bynum INFORMS Journal on Computing 35 (2), 509-517, 2023 | 28 | 2023 |
| Parmest: Parameter estimation via pyomo KA Klise, BL Nicholson, A Staid, DL Woodruff Computer Aided Chemical Engineering 47, 41-46, 2019 | 25 | 2019 |
| Sensor placement optimization software applied to site-scale methane-emissions monitoring KA Klise, BL Nicholson, CD Laird, AP Ravikumar, AR Brandt Journal of Environmental Engineering 146 (7), 04020054, 2020 | 21 | 2020 |
| Parallel cyclic reduction decomposition for dynamic optimization problems W Wan, JP Eason, B Nicholson, LT Biegler Computers & Chemical Engineering 120, 54-69, 2019 | 17 | 2019 |
| Equation-based and data-driven modeling: Open-source software current state and future directions LG Gunnell, B Nicholson, JD Hedengren Computers & Chemical Engineering 181, 108521, 2024 | 14 | 2024 |
| An implicit function formulation for optimization of discretized index-1 differential algebraic systems R Parker, B Nicholson, J Siirola, C Laird, L Biegler Computers & Chemical Engineering 168, 108042, 2022 | 14 | 2022 |
| Applications of the Dulmage–Mendelsohn decomposition for debugging nonlinear optimization problems RB Parker, BL Nicholson, JD Siirola, LT Biegler Computers & Chemical Engineering 178, 108383, 2023 | 12 | 2023 |
| Pyomo-Optimization Modeling in Python 3rd Ed. ML Bynum, G Hackebeil, WE Hart, CD Laird, BL Nicholson, JD Siirola, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2020 | 9 | 2020 |
| Optimal mitigation and control over power system dynamics for stochastic grid resilience N Stewart, B Arguello, M Hoffman, B Nicholson, R Garrett Optimization and Engineering 25 (2), 911-940, 2024 | 8 | 2024 |
| Parallel cyclic reduction strategies for linear systems that arise in dynamic optimization problems BL Nicholson, W Wan, S Kameswaran, LT Biegler Computational Optimization and Applications 70 (2), 321-350, 2018 | 8 | 2018 |
| Pyomo–optimization Modeling in python, vol. 67 WE Hartand, CD Laird, J Watson, DL Woodruff, GA Hackebei, ... Springer Science & Business Media, 2017 | 6 | 2017 |
| Model predictive control simulations with block-hierarchical differential–algebraic process models RB Parker, BL Nicholson, JD Siirola, LT Biegler Journal of Process Control 132, 103113, 2023 | 5 | 2023 |
Jean-Paul WatsonLawrence Livermore National Laboratory, Livermore, California, USAVerified email at llnl.gov
