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ORCIDAlexander Mitsos
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- affiliation: RWTH Aachen University, Germany
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2020 – today
- 2025
[j85]Georgia Ioanna Prokopou
, Johannes M. M. Faust, Alexander Mitsos, Dominik Bongartz:
Cost-optimal design and operation of hydrogen refueling stations with mechanical and electrochemical hydrogen compressors. Comput. Chem. Eng. 192: 108862 (2025)- 2024
- [j84]Moein E. Samadi, Hedieh Mirzaieazar, Alexander Mitsos, Andreas Schuppert:
Noisecut: a python package for noise-tolerant classification of binary data using prior knowledge integration and max-cut solutions. BMC Bioinform. 25(1): 155 (2024) - [j83]Moritz J. Begall, Frank Herbstritt, Anne-Laura Sengen, Adel Mhamdi, Joachim Heck, Alexander Mitsos:
Hierarchical heat transfer modeling of a continuous millireactor. Comput. Chem. Eng. 183: 108621 (2024) - [j82]Sonja H. M. Germscheid, Benedikt Nilges, Niklas von der Aßen, Alexander Mitsos, Manuel Dahmen:
Optimal design of a local renewable electricity supply system for power-intensive production processes with demand response. Comput. Chem. Eng. 185: 108656 (2024) - [j81]Daniel Mayfrank, Alexander Mitsos, Manuel Dahmen:
End-to-end reinforcement learning of Koopman models for economic nonlinear model predictive control. Comput. Chem. Eng. 190: 108824 (2024) - [j80]Susanne Sass, Alexander Mitsos, Dominik Bongartz, Ian H. Bell, Nikolay I. Nikolov, Angelos Tsoukalas:
A branch-and-bound algorithm with growing datasets for large-scale parameter estimation. Eur. J. Oper. Res. 316(1): 36-45 (2024) - [j79]Danimir T. Doncevic, Alexander Mitsos, Yue Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, Ioannis G. Kevrekidis:
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms. SIAM J. Sci. Comput. 46(2): 719- (2024) - [i25]Christoforos Brozos, Jan G. Rittig, Sandip Bhattacharya, Elie Akanny, Christina Kohlmann, Alexander Mitsos:
Graph Neural Networks for Surfactant Multi-Property Prediction. CoRR abs/2401.01874 (2024) - [i24]Jan C. Schulze, Alexander Mitsos:
Data-driven Nonlinear Model Reduction using Koopman Theory: Integrated Control Form and NMPC Case Study. CoRR abs/2401.04508 (2024) - [i23]Christoforos Brozos, Jan G. Rittig, Sandip Bhattacharya, Elie Akanny, Christina Kohlmann, Alexander Mitsos:
Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks. CoRR abs/2403.03767 (2024) - [i22]Eleni D. Koronaki, Luise F. Kaven, Johannes M. M. Faust, Ioannis G. Kevrekidis, Alexander Mitsos:
Nonlinear Manifold Learning Determines Microgel Size from Raman Spectroscopy. CoRR abs/2403.08376 (2024) - [i21]Daniel Mayfrank, Na-Young Ahn, Alexander Mitsos, Manuel Dahmen:
Task-optimal data-driven surrogate models for eNMPC via differentiable simulation and optimization. CoRR abs/2403.14425 (2024) - [i20]Chrysanthi Papadimitriou, Jan C. Schulze, Alexander Mitsos:
Representative electricity price profiles for European day-ahead and intraday spot markets. CoRR abs/2405.14403 (2024) - [i19]Mehmet Velioglu, Song Zhai, Sophia Rupprecht, Alexander Mitsos, Andreas Jupke, Manuel Dahmen:
Physics-Informed Neural Networks for Dynamic Process Operations with Limited Physical Knowledge and Data. CoRR abs/2406.01528 (2024) - [i18]Jan G. Rittig, Alexander Mitsos:
Thermodynamics-Consistent Graph Neural Networks. CoRR abs/2407.18372 (2024) - 2023
- [j78]Moritz J. Begall, Artur M. Schweidtmann, Adel Mhamdi, Alexander Mitsos:
Geometry optimization of a continuous millireactor via CFD and Bayesian optimization. Comput. Chem. Eng. 171: 108140 (2023) - [j77]Jan G. Rittig, Karim Ben Hicham, Artur M. Schweidtmann, Manuel Dahmen, Alexander Mitsos:
Graph neural networks for temperature-dependent activity coefficient prediction of solutes in ionic liquids. Comput. Chem. Eng. 171: 108153 (2023) - [j76]Artur M. Schweidtmann, Jan G. Rittig, Jana M. Weber, Martin Grohe, Manuel Dahmen, Kai Leonhard, Alexander Mitsos:
Physical pooling functions in graph neural networks for molecular property prediction. Comput. Chem. Eng. 172: 108202 (2023) - [j75]Simone Mucci, Alexander Mitsos, Dominik Bongartz:
Power-to-X processes based on PEM water electrolyzers: A review of process integration and flexible operation. Comput. Chem. Eng. 175: 108260 (2023) - [j74]Sonja H. M. Germscheid, Fritz T. C. Röben, Han Sun, André Bardow, Alexander Mitsos, Manuel Dahmen:
Demand response scheduling of copper production under short-term electricity price uncertainty. Comput. Chem. Eng. 178: 108394 (2023) - [j73]Susanne Sass, Angelos Tsoukalas, Ian H. Bell, Dominik Bongartz, Jaromil Najman, Alexander Mitsos:
Towards global parameter estimation exploiting reduced data sets. Optim. Methods Softw. 38(6): 1129-1141 (2023) - [d1]Artur M. Schweidtmann, Jan G. Rittig, Jana M. Weber, Martin Grohe, Manuel Dahmen, Kai Leonhard, Alexander Mitsos:
Software for "Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction". Zenodo, 2023
- [i17]Jan G. Rittig, Kobi C. Felton, Alexei A. Lapkin, Alexander Mitsos:
Gibbs-Duhem-Informed Neural Networks for Binary Activity Coefficient Prediction. CoRR abs/2306.07937 (2023) - [i16]Daniel Mayfrank, Alexander Mitsos, Manuel Dahmen:
End-to-End Reinforcement Learning of Koopman Models for Economic Nonlinear Model Predictive Control. CoRR abs/2308.01674 (2023) - [i15]Luise F. Kaven, Artur M. Schweidtmann, Jan Keil, Jana Israel, Nadja Wolter, Alexander Mitsos:
Data-driven Product-Process Optimization of N-isopropylacrylamide Microgel Flow-Synthesis. CoRR abs/2308.16724 (2023) - [i14]Jan C. Schulze, Danimir T. Doncevic, Nils Erwes, Alexander Mitsos:
Data-Driven Model Reduction and Nonlinear Model Predictive Control of an Air Separation Unit by Applied Koopman Theory. CoRR abs/2309.05386 (2023) - 2022
- [j72]Eike Cramer, Leonardo Rydin Gorjão, Alexander Mitsos, Benjamin Schäfer, Dirk Witthaut, Manuel Dahmen:
Validation Methods for Energy Time Series Scenarios From Deep Generative Models. IEEE Access 10: 8194-8207 (2022) - [j71]Tim Varelmann, Nils Erwes, Pascal Schäfer, Alexander Mitsos:
Simultaneously optimizing bidding strategy in pay-as-bid-markets and production scheduling. Comput. Chem. Eng. 157: 107610 (2022) - [j70]Tim Varelmann, Adrian W. Lipow, Michael Baldea, Alexander Mitsos:
Advanced feasibility cuts in decoupled cooperative optimization of power flow. Comput. Chem. Eng. 157: 107635 (2022) - [j69]Tobias Ploch, Jens Deussen, Uwe Naumann, Alexander Mitsos, Ralf Hannemann-Tamás:
Direct single shooting for dynamic optimization of differential-algebraic equation systems with optimization criteria embedded. Comput. Chem. Eng. 159: 107643 (2022) - [j68]Kilian Merkelbach, Artur M. Schweidtmann, Younes Müller, Patrick Schwoebel, Adel Mhamdi, Alexander Mitsos, Andreas Schuppert, Thomas Mrziglod, Sebastian Schneckener:
HybridML: Open source platform for hybrid modeling. Comput. Chem. Eng. 160: 107736 (2022) - [j67]Marco Langiu, Manuel Dahmen, Alexander Mitsos:
Simultaneous optimization of design and operation of an air-cooled geothermal ORC under consideration of multiple operating points. Comput. Chem. Eng. 161: 107745 (2022) - [j66]Jan C. Schulze, Danimir T. Doncevic, Alexander Mitsos:
Identification of MIMO Wiener-type Koopman models for data-driven model reduction using deep learning. Comput. Chem. Eng. 161: 107781 (2022) - [j65]Steffen Fahr, Alexander Mitsos, Dominik Bongartz:
Simultaneous deterministic global flowsheet optimization and heat integration: Comparison of formulations. Comput. Chem. Eng. 162: 107790 (2022) - [j64]Jannik Burre, Christoph Kabatnik, Mohamed Al-Khatib, Dominik Bongartz, Andreas Jupke, Alexander Mitsos:
Global flowsheet optimization for reductive dimethoxymethane production using data-driven thermodynamic models. Comput. Chem. Eng. 162: 107806 (2022) - [j63]Eduardo S. Schultz, Simon Olofsson, Adel Mhamdi, Alexander Mitsos:
Satisfaction of path chance constraints in dynamic optimization problems. Comput. Chem. Eng. 164: 107899 (2022) - [j62]Eike Cramer, Leonard Paeleke, Alexander Mitsos, Manuel Dahmen:
Normalizing flow-based day-ahead wind power scenario generation for profitable and reliable delivery commitments by wind farm operators. Comput. Chem. Eng. 166: 107923 (2022) - [j61]Andreas M. Bremen, Katharina M. Ebeling, Victor Schulte, Jan Pavsek, Alexander Mitsos:
Dynamic modeling of aqueous electrolyte systems in Modelica. Comput. Chem. Eng. 166: 107968 (2022) - [j60]Jan C. Schulze, Alexander Mitsos:
Data-Driven Nonlinear Model Reduction Using Koopman Theory: Integrated Control Form and NMPC Case Study. IEEE Control. Syst. Lett. 6: 2978-2983 (2022) - [j59]Chrysoula Dimitra Kappatou, Dominik Bongartz, Jaromil Najman, Susanne Sass, Alexander Mitsos:
Global dynamic optimization with Hammerstein-Wiener models embedded. J. Glob. Optim. 84(2): 321-347 (2022) - [j58]Daniel Jungen, Hatim Djelassi, Alexander Mitsos:
Adaptive discretization-based algorithms for semi-infinite programs with unbounded variables. Math. Methods Oper. Res. 96(1): 83-112 (2022) - [j57]Adrian Caspari, Steffen Fahr, Alexander Mitsos:
Optimal Eco-Routing for Hybrid Vehicles With Powertrain Model Embedded. IEEE Trans. Intell. Transp. Syst. 23(9): 14632-14648 (2022) - [i13]Jan C. Schulze, Danimir T. Doncevic, Alexander Mitsos:
Identification of MIMO Wiener-type Koopman Models for Data-Driven Model Reduction using Deep Learning. CoRR abs/2201.12669 (2022) - [i12]Eike Cramer, Felix Rauh, Alexander Mitsos, Raúl Tempone, Manuel Dahmen:
Nonlinear Isometric Manifold Learning for Injective Normalizing Flows. CoRR abs/2203.03934 (2022) - [i11]Eike Cramer, Leonard Paeleke, Alexander Mitsos, Manuel Dahmen:
Normalizing Flow-based Day-Ahead Wind Power Scenario Generation for Profitable and Reliable Delivery Commitments by Wind Farm Operators. CoRR abs/2204.02242 (2022) - [i10]Eike Cramer, Dirk Witthaut, Alexander Mitsos, Manuel Dahmen:
Multivariate Probabilistic Forecasting of Intraday Electricity Prices using Normalizing Flows. CoRR abs/2205.13826 (2022) - [i9]Jan G. Rittig, Martin Ritzert, Artur M. Schweidtmann, Stefanie Winkler, Jana M. Weber, Philipp Morsch, K. Alexander Heufer, Martin Grohe, Alexander Mitsos, Manuel Dahmen:
Graph Machine Learning for Design of High-Octane Fuels. CoRR abs/2206.00619 (2022) - [i8]Jan G. Rittig, Karim Ben Hicham, Artur M. Schweidtmann, Manuel Dahmen, Alexander Mitsos:
Graph Neural Networks for Temperature-Dependent Activity Coefficient Prediction of Solutes in Ionic Liquids. CoRR abs/2206.11776 (2022) - [i7]Artur M. Schweidtmann, Jan G. Rittig, Jana M. Weber, Martin Grohe, Manuel Dahmen, Kai Leonhard, Alexander Mitsos:
Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction. CoRR abs/2207.13779 (2022) - [i6]Jan G. Rittig, Qinghe Gao, Manuel Dahmen, Alexander Mitsos, Artur M. Schweidtmann:
Graph neural networks for the prediction of molecular structure-property relationships. CoRR abs/2208.04852 (2022) - [i5]Danimir T. Doncevic, Alexander Mitsos, Yue Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, Ioannis G. Kevrekidis:
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms. CoRR abs/2211.12386 (2022) - 2021
- [j56]Jan C. Schulze, Adrian Caspari, Christoph Offermanns, Adel Mhamdi, Alexander Mitsos:
Nonlinear model predictive control of ultra-high-purity air separation units using transient wave propagation model. Comput. Chem. Eng. 145: 107163 (2021) - [j55]Efstratios N. Pistikopoulos, Ana Barbosa-Póvoa, Jay H. Lee, Ruth Misener, Alexander Mitsos, Gintaras V. Reklaitis, Venkat Venkatasubramanian, Fengqi You, Rafiqul Gani:
Process systems engineering - The generation next?. Comput. Chem. Eng. 147: 107252 (2021) - [j54]Marco Langiu, David Yang Shu, Florian Joseph Baader, Dominik Hering, Uwe Bau, André Xhonneux, Dirk Müller, André Bardow, Alexander Mitsos, Manuel Dahmen:
COMANDO: A Next-Generation Open-Source Framework for Energy Systems Optimization. Comput. Chem. Eng. 152: 107366 (2021) - [j53]Hatim Djelassi, Alexander Mitsos, Oliver Stein:
Recent advances in nonconvex semi-infinite programming: Applications and algorithms. EURO J. Comput. Optim. 9: 100006 (2021) - [j52]Ulf W. Liebal, Sebastian Köbbing, Linus Netze, Artur M. Schweidtmann, Alexander Mitsos, Lars M. Blank:
Insight to Gene Expression From Promoter Libraries With the Machine Learning Workflow Exp2Ipynb. Frontiers Bioinform. 1 (2021) - [j51]Jaromil Najman, Dominik Bongartz, Alexander Mitsos:
Linearization of McCormick relaxations and hybridization with the auxiliary variable method. J. Glob. Optim. 80(4): 731-756 (2021) - [j50]Hatim Djelassi, Alexander Mitsos:
Global Solution of Semi-infinite Programs with Existence Constraints. J. Optim. Theory Appl. 188(3): 863-881 (2021) - [j49]Artur M. Schweidtmann, Dominik Bongartz, Daniel Grothe, Tim Kerkenhoff, Xiaopeng Lin, Jaromil Najman, Alexander Mitsos:
Deterministic global optimization with Gaussian processes embedded. Math. Program. Comput. 13(3): 553-581 (2021) - [i4]Simon Olofsson, Eduardo S. Schultz, Adel Mhamdi, Alexander Mitsos, Marc Peter Deisenroth, Ruth Misener:
Design of Dynamic Experiments for Black-Box Model Discrimination. CoRR abs/2102.03782 (2021) - [i3]Eike Cramer, Alexander Mitsos, Raúl Tempone, Manuel Dahmen:
Principal Component Density Estimation for Scenario Generation Using Normalizing Flows. CoRR abs/2104.10410 (2021) - [i2]Eike Cramer, Leonardo Rydin Gorjão, Alexander Mitsos, Benjamin Schäfer, Dirk Witthaut, Manuel Dahmen:
Validation Methods for Energy Time Series Scenarios from Deep Generative Models. CoRR abs/2110.14451 (2021) - 2020
- [j48]Eduardo S. Schultz, Ralf Hannemann-Tamás, Alexander Mitsos:
Guaranteed satisfaction of inequality state constraints in PDE-constrained optimization. Autom. 111 (2020) - [j47]Enio Gjerga, Panuwat Trairatphisan, Attila Gábor, Hermann Koch, Céline Chevalier, Franceco Ceccarelli, Aurélien Dugourd, Alexander Mitsos, Julio Saez-Rodriguez, Jonathan D. Wren:
Converting networks to predictive logic models from perturbation signalling data with CellNOpt. Bioinform. 36(16): 4523-4524 (2020) - [j46]Pascal Schäfer, Artur M. Schweidtmann, Philipp H. A. Lenz, Hannah M. C. Markgraf, Alexander Mitsos:
Wavelet-based grid-adaptation for nonlinear scheduling subject to time-variable electricity prices. Comput. Chem. Eng. 132 (2020) - [j45]Andrea König, Lisa Neidhardt, Jörn Viell, Alexander Mitsos, Manuel Dahmen:
Integrated design of processes and products: Optimal renewable fuels. Comput. Chem. Eng. 134: 106712 (2020) - [j44]Eduardo S. Schultz, Ralf Hannemann-Tamás, Alexander Mitsos:
Polynomial approximation of inequality path constraints in dynamic optimization. Comput. Chem. Eng. 135: 106732 (2020) - [j43]Susanne Sass, Timm Faulwasser, Dinah Elena Hollermann, Chrysoula Dimitra Kappatou, Dominique Sauer, Thomas Schütz, David Yang Shu, André Bardow, Lutz Gröll, Veit Hagenmeyer, Dirk Müller, Alexander Mitsos:
Model compendium, data, and optimization benchmarks for sector-coupled energy systems. Comput. Chem. Eng. 135: 106760 (2020) - [j42]Luisa C. Brée, Matthias Wessling, Alexander Mitsos:
Modular modeling of electrochemical reactors: Comparison of CO2-electolyzers. Comput. Chem. Eng. 139: 106890 (2020) - [j41]Adrian Caspari, Lukas Lüken, Pascal Schäfer, Yannic Vaupel, Adel Mhamdi, Lorenz T. Biegler, Alexander Mitsos:
Dynamic optimization with complementarity constraints: Smoothing for direct shooting. Comput. Chem. Eng. 139: 106891 (2020) - [j40]Tobias Ploch, Eric von Lieres, Wolfgang Wiechert, Alexander Mitsos, Ralf Hannemann-Tamás:
Simulation of differential-algebraic equation systems with optimization criteria embedded in Modelica. Comput. Chem. Eng. 140: 106920 (2020) - [j39]Preet Joy, Adel Mhamdi, Alexander Mitsos:
Optimization-based observability analysis. Comput. Chem. Eng. 140: 106932 (2020) - [j38]Wolfgang R. Huster, Artur M. Schweidtmann, Jannik T. Lüthje, Alexander Mitsos:
Deterministic global superstructure-based optimization of an organic Rankine cycle. Comput. Chem. Eng. 141: 106996 (2020) - [j37]Chrysoula Dimitra Kappatou, Alireza Ehsani, Sebastian Niedenführ, Adel Mhamdi, Andreas Schuppert, Alexander Mitsos:
Quality-targeting dynamic optimization of monoclonal antibody production. Comput. Chem. Eng. 142: 107004 (2020) - [i1]Artur M. Schweidtmann, Dominik Bongartz, Daniel Grothe, Tim Kerkenhoff, Xiaopeng Lin, Jaromil Najman, Alexander Mitsos:
Global Optimization of Gaussian processes. CoRR abs/2005.10902 (2020)
2010 – 2019
- 2019
- [j36]Pascal Schäfer, Hermann Graf Westerholt, Artur M. Schweidtmann, Svetlina Ilieva, Alexander Mitsos:
Model-based bidding strategies on the primary balancing market for energy-intense processes. Comput. Chem. Eng. 120: 4-14 (2019) - [j35]Artur M. Schweidtmann, Wolfgang R. Huster, Jannik T. Lüthje, Alexander Mitsos:
Deterministic global process optimization: Accurate (single-species) properties via artificial neural networks. Comput. Chem. Eng. 121: 67-74 (2019) - [j34]Susanne Sass, Alexander Mitsos:
Optimal operation of dynamic (energy) systems: When are quasi-steady models adequate? Comput. Chem. Eng. 124: 133-139 (2019) - [j33]Preet Joy, Hatim Djelassi, Adel Mhamdi, Alexander Mitsos:
Optimization-based global structural identifiability. Comput. Chem. Eng. 128: 417-420 (2019) - [j32]Johannes M. M. Faust, Tomas Chaloupka, Juraj Kosek, Adel Mhamdi, Alexander Mitsos:
Dynamic optimization of an emulsion copolymerization process for product quality using a deterministic kinetic model with embedded Monte Carlo simulations. Comput. Chem. Eng. 130 (2019) - [j31]Jaromil Najman, Dominik Bongartz, Alexander Mitsos:
Convex relaxations of componentwise convex functions. Comput. Chem. Eng. 130 (2019) - [j30]Jaromil Najman, Dominik Bongartz, Alexander Mitsos:
Relaxations of thermodynamic property and costing models in process engineering. Comput. Chem. Eng. 130 (2019) - [j29]Alexander Mitsos, Jaromil Najman, Ioannis G. Kevrekidis:
Correction to: Optimal deterministic algorithm generation. J. Glob. Optim. 73(2): 465 (2019) - [j28]Jaromil Najman, Alexander Mitsos:
On tightness and anchoring of McCormick and other relaxations. J. Glob. Optim. 74(4): 677-703 (2019) - [j27]Hatim Djelassi, Moll Glass, Alexander Mitsos:
Discretization-based algorithms for generalized semi-infinite and bilevel programs with coupling equality constraints. J. Glob. Optim. 75(2): 341-392 (2019) - [j26]Jaromil Najman, Alexander Mitsos:
Tighter McCormick relaxations through subgradient propagation. J. Glob. Optim. 75(3): 565-593 (2019) - [j25]Artur M. Schweidtmann, Alexander Mitsos:
Deterministic Global Optimization with Artificial Neural Networks Embedded. J. Optim. Theory Appl. 180(3): 925-948 (2019) - 2018
- [j24]Olga Walz, Hatim Djelassi, Adrian Caspari, Alexander Mitsos:
Bounded-error optimal experimental design via global solution of constrained min-max program. Comput. Chem. Eng. 111: 92-101 (2018) - [j23]Alexander Mitsos, Norbert Asprion, Christodoulos A. Floudas, Michael Bortz, Michael Baldea, Dominique Bonvin, Adrian Caspari, Pascal Schäfer:
Challenges in process optimization for new feedstocks and energy sources. Comput. Chem. Eng. 113: 209-221 (2018) - [j22]Jennifer Puschke, Hatim Djelassi, Johanna Kleinekorte, Ralf Hannemann-Tamás, Alexander Mitsos:
Robust dynamic optimization of batch processes under parametric uncertainty: Utilizing approaches from semi-infinite programs. Comput. Chem. Eng. 116: 253-267 (2018) - [j21]Alexander Mitsos, Jaromil Najman, Ioannis G. Kevrekidis:
Optimal deterministic algorithm generation. J. Glob. Optim. 71(4): 891-913 (2018) - 2017
- [j20]Olga Walz, Caroline Marks, Jörn Viell, Alexander Mitsos:
Systematic approach for modeling reaction networks involving equilibrium and kinetically-limited reaction steps. Comput. Chem. Eng. 98: 143-153 (2017) - [j19]Jennifer Puschke, Alexandr Zubov, Juraj Kosek, Alexander Mitsos:
Multi-model approach based on parametric sensitivities - A heuristic approximation for dynamic optimization of semi-batch processes with parametric uncertainties. Comput. Chem. Eng. 98: 161-179 (2017) - [j18]Moll Glass, Alexander Mitsos:
Thermodynamic analysis of formulations to discriminate multiple roots of cubic equations of state in process models. Comput. Chem. Eng. 106: 407-420 (2017) - [j17]Jaromil Najman, Dominik Bongartz, Angelos Tsoukalas, Alexander Mitsos:
Erratum to: Multivariate McCormick relaxations. J. Glob. Optim. 68(1): 219-225 (2017) - [j16]Hatim Djelassi, Alexander Mitsos:
A hybrid discretization algorithm with guaranteed feasibility for the global solution of semi-infinite programs. J. Glob. Optim. 68(2): 227-253 (2017) - [j15]Dominik Bongartz, Alexander Mitsos:
Deterministic global optimization of process flowsheets in a reduced space using McCormick relaxations. J. Glob. Optim. 69(4): 761-796 (2017) - 2016
- [j14]Jaromil Najman, Alexander Mitsos:
Convergence analysis of multivariate McCormick relaxations. J. Glob. Optim. 66(4): 597-628 (2016) - 2015
- [j13]Jun Fu, Johannes M. M. Faust, Benoît Chachuat, Alexander Mitsos:
Local optimization of dynamic programs with guaranteed satisfaction of path constraints. Autom. 62: 184-192 (2015) - [j12]Alexander Mitsos, Angelos Tsoukalas:
Global optimization of generalized semi-infinite programs via restriction of the right hand side. J. Glob. Optim. 61(1): 1-17 (2015) - [c2]Johannes Lotz, Uwe Naumann, Ralf Hannemann-Tamás, Tobias Ploch, Alexander Mitsos:
Higher-order Discrete Adjoint ODE Solver in C++ for Dynamic Optimization. ICCS 2015: 256-265 - 2014
- [j11]Angelos Tsoukalas, Alexander Mitsos:
Multivariate McCormick relaxations. J. Glob. Optim. 59(2-3): 633-662 (2014) - 2013
- [j10]Agustín Bompadre, Alexander Mitsos, Benoît Chachuat:
Convergence analysis of Taylor models and McCormick-Taylor models. J. Glob. Optim. 57(1): 75-114 (2013) - 2012
- [j9]Agustín Bompadre, Alexander Mitsos:
Convergence rate of McCormick relaxations. J. Glob. Optim. 52(1): 1-28 (2012) - 2011
- [j8]Ioannis N. Melas, Alexander Mitsos, Dimitris E. Messinis, Thomas S. Weiss, Leonidas G. Alexopoulos:
Combined logical and data-driven models for linking signalling pathways to cellular response. BMC Syst. Biol. 5: 107 (2011) - [c1]Ioannis N. Melas, Aikaterini D. Chairakaki, Alexander Mitsos, Zoe Dailiana, Christopher G. Provatidis, Leonidas G. Alexopoulos:
Modeling signaling pathways in articular cartilage. EMBC 2011: 3712-3715 - 2010
- [j7]Alexander Mitsos:
Global solution of nonlinear mixed-integer bilevel programs. J. Glob. Optim. 47(4): 557-582 (2010)
2000 – 2009
- 2009
- [j6]Alexander Mitsos, Paul I. Barton:
Parametric mixed-integer 0-1 linear programming: The general case for a single parameter. Eur. J. Oper. Res. 194(3): 663-686 (2009) - [j5]Alexander Mitsos, Benoît Chachuat, Paul I. Barton:
Towards global bilevel dynamic optimization. J. Glob. Optim. 45(1): 63-93 (2009) - [j4]Alexander Mitsos, Ioannis N. Melas, Paraskeuas Siminelakis, Aikaterini D. Chairakaki, Julio Saez-Rodriguez, Leonidas G. Alexopoulos:
Identifying Drug Effects via Pathway Alterations using an Integer Linear Programming Optimization Formulation on Phosphoproteomic Data. PLoS Comput. Biol. 5(12) (2009) - [j3]Alexander Mitsos, Benoît Chachuat, Paul I. Barton:
McCormick-Based Relaxations of Algorithms. SIAM J. Optim. 20(2): 573-601 (2009) - 2008
- [j2]Alexander Mitsos, Panayiotis Lemonidis, Paul I. Barton:
Global solution of bilevel programs with a nonconvex inner program. J. Glob. Optim. 42(4): 475-513 (2008) - [j1]Alexander Mitsos, Panayiotis Lemonidis, Cha Kun Lee, Paul I. Barton:
Relaxation-Based Bounds for Semi-Infinite Programs. SIAM J. Optim. 19(1): 77-113 (2008)
Coauthor Index
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last updated on 2024-10-07 21:20 CEST by the dblp team
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