| A two-layer architecture for economically optimal process control and operation L Würth, R Hannemann, W Marquardt Journal of Process Control 21 (3), 311-321, 2011 | 162 | 2011 |
| Neighboring-extremal updates for nonlinear model-predictive control and dynamic real-time optimization L Würth, R Hannemann, W Marquardt Journal of Process Control 19 (8), 1277-1288, 2009 | 111 | 2009 |
| Continuous and discrete composite adjoints for the Hessian of the Lagrangian in shooting algorithms for dynamic optimization R Hannemann, W Marquardt SIAM journal on scientific computing 31 (6), 4675-4695, 2010 | 51 | 2010 |
| Discrete first-and second-order adjoints and automatic differentiation for the sensitivity analysis of dynamic models R Hannemann, W Marquardt, U Naumann, B Gendler Procedia Computer Science 1 (1), 297-305, 2010 | 48 | 2010 |
| Incremental single shooting—a robust method for the estimation of parameters in dynamical systems C Michalik, R Hannemann, W Marquardt Computers & Chemical Engineering 33 (7), 1298-1305, 2009 | 45 | 2009 |
| Dyos-a framework for optimization of large-scale differential algebraic equation systems A Caspari, AM Bremen, JMM Faust, F Jung, CD Kappatou, S Sass, ... Computer Aided Chemical Engineering 46, 619-624, 2019 | 44 | 2019 |
| An iterative partition-based moving horizon estimator with coupled inequality constraints R Schneider, R Hannemann-Tamás, W Marquardt Automatica 61, 302-307, 2015 | 39 | 2015 |
| How to verify optimal controls computed by direct shooting methods?–A tutorial R Hannemann-Tamás, W Marquardt Journal of process control 22 (2), 494-507, 2012 | 34 | 2012 |
| Optimized Hollow Fiber Sorbents and Pressure Swing Adsorption Process for H2 Recovery B Ohs, J Lohaus, D Marten, R Hannemann-Tamás, A Krieger, M Wessling Industrial & Engineering Chemistry Research 57 (14), 5093-5105, 2018 | 27 | 2018 |
| Robust dynamic optimization of batch processes under parametric uncertainty: Utilizing approaches from semi-infinite programs J Puschke, H Djelassi, J Kleinekorte, R Hannemann-Tamás, A Mitsos Computers & Chemical Engineering 116, 253-267, 2018 | 25 | 2018 |
| Model complexity reduction of chemical reaction networks using mixed-integer quadratic programming R Hannemann-Tamás, A Gabor, G Szederkenyi, KM Hangos Computers & Mathematics with Applications 65 (10), 1575-1595, 2013 | 23 | 2013 |
| Higher-order discrete adjoint ODE solver in C++ for dynamic optimization J Lotz, U Naumann, R Hannemann-Taḿas, T Ploch, A Mitsos Procedia Computer Science 51, 256-265, 2015 | 15 | 2015 |
| Multiscale dynamic modeling and simulation of a biorefinery T Ploch, X Zhao, J Hüser, E von Lieres, R Hannemann‐Tamás, ... Biotechnology and Bioengineering 116 (10), 2561-2574, 2019 | 14 | 2019 |
| Simulation of differential-algebraic equation systems with optimization criteria embedded in Modelica T Ploch, E von Lieres, W Wiechert, A Mitsos, R Hannemann-Tamás Computers & Chemical Engineering 140, 106920, 2020 | 13 | 2020 |
| Adjoint sensitivity analysis for nonsmooth differential-algebraic equation systems R Hannemann-Tamas, DA Munoz, W Marquardt SIAM Journal on Scientific Computing 37 (5), A2380-A2402, 2015 | 11 | 2015 |
| Fast computation of the Hessian of the Lagrangian in shooting algorithms for dynamic optimization R Hannemann, W Marquardt Proceedings of the 8th International IFAC Symposium on Dynamics and Control …, 2007 | 11 | 2007 |
| Adjoint Sensitivity Analysis for Optimal Control of Non-Smooth Differential-Algebraic Equations R Hannemann-Tamás Shaker, 2013 | 10 | 2013 |
| Modeling of dynamic systems with a variable number of phases in liquid–liquid equilibria T Ploch, M Glass, AM Bremen, R Hannemann‐Tamás, A Mitsos AIChE Journal 65 (2), 571-581, 2019 | 9 | 2019 |
| Polynomial approximation of inequality path constraints in dynamic optimization ES Schultz, R Hannemann-Tamás, A Mitsos Computers & Chemical Engineering 135, 106732, 2020 | 8 | 2020 |
| Model-based investment planning model for stepwise capacity expansions of chemical plants A Wiesner, M Schlegel, J Oldenburg, L Würth, R Hannemann, A Polt Computer Aided Chemical Engineering 25, 307-312, 2008 | 8 | 2008 |
Uwe NaumannProfessor for Computer Science, RWTH AachenVerified email at stce.rwth-aachen.de
