---
_id: '21940'
author:
- first_name: Florian
full_name: Litzinger, Florian
last_name: Litzinger
- first_name: Lorenzo
full_name: Boninsegna, Lorenzo
last_name: Boninsegna
- first_name: Hao
full_name: Wu, Hao
last_name: Wu
- first_name: Feliks
full_name: Nüske, Feliks
id: '81513'
last_name: Nüske
orcid: 0000-0003-2444-7889
- first_name: Raajen
full_name: Patel, Raajen
last_name: Patel
- first_name: Richard
full_name: Baraniuk, Richard
last_name: Baraniuk
- first_name: Frank
full_name: Noé, Frank
last_name: Noé
- first_name: Cecilia
full_name: Clementi, Cecilia
last_name: Clementi
citation:
ama: Litzinger F, Boninsegna L, Wu H, et al. Rapid Calculation of Molecular Kinetics
Using Compressed Sensing. Journal of Chemical Theory and Computation. 2018:2771-2783.
doi:10.1021/acs.jctc.8b00089
apa: Litzinger, F., Boninsegna, L., Wu, H., Nüske, F., Patel, R., Baraniuk, R.,
… Clementi, C. (2018). Rapid Calculation of Molecular Kinetics Using Compressed
Sensing. Journal of Chemical Theory and Computation, 2771–2783. https://doi.org/10.1021/acs.jctc.8b00089
bibtex: '@article{Litzinger_Boninsegna_Wu_Nüske_Patel_Baraniuk_Noé_Clementi_2018,
title={Rapid Calculation of Molecular Kinetics Using Compressed Sensing}, DOI={10.1021/acs.jctc.8b00089},
journal={Journal of Chemical Theory and Computation}, author={Litzinger, Florian
and Boninsegna, Lorenzo and Wu, Hao and Nüske, Feliks and Patel, Raajen and Baraniuk,
Richard and Noé, Frank and Clementi, Cecilia}, year={2018}, pages={2771–2783}
}'
chicago: Litzinger, Florian, Lorenzo Boninsegna, Hao Wu, Feliks Nüske, Raajen Patel,
Richard Baraniuk, Frank Noé, and Cecilia Clementi. “Rapid Calculation of Molecular
Kinetics Using Compressed Sensing.” Journal of Chemical Theory and Computation,
2018, 2771–83. https://doi.org/10.1021/acs.jctc.8b00089.
ieee: F. Litzinger et al., “Rapid Calculation of Molecular Kinetics Using
Compressed Sensing,” Journal of Chemical Theory and Computation, pp. 2771–2783,
2018.
mla: Litzinger, Florian, et al. “Rapid Calculation of Molecular Kinetics Using Compressed
Sensing.” Journal of Chemical Theory and Computation, 2018, pp. 2771–83,
doi:10.1021/acs.jctc.8b00089.
short: F. Litzinger, L. Boninsegna, H. Wu, F. Nüske, R. Patel, R. Baraniuk, F. Noé,
C. Clementi, Journal of Chemical Theory and Computation (2018) 2771–2783.
date_created: 2021-04-30T16:58:07Z
date_updated: 2022-01-06T06:55:20Z
department:
- _id: '101'
doi: 10.1021/acs.jctc.8b00089
extern: '1'
language:
- iso: eng
page: 2771-2783
publication: Journal of Chemical Theory and Computation
publication_identifier:
issn:
- 1549-9618
- 1549-9626
publication_status: published
status: public
title: Rapid Calculation of Molecular Kinetics Using Compressed Sensing
type: journal_article
user_id: '81513'
year: '2018'
...
---
_id: '21941'
author:
- first_name: Stefan
full_name: Klus, Stefan
last_name: Klus
- first_name: Feliks
full_name: Nüske, Feliks
id: '81513'
last_name: Nüske
orcid: 0000-0003-2444-7889
- first_name: Péter
full_name: Koltai, Péter
last_name: Koltai
- first_name: Hao
full_name: Wu, Hao
last_name: Wu
- first_name: Ioannis
full_name: Kevrekidis, Ioannis
last_name: Kevrekidis
- first_name: Christof
full_name: Schütte, Christof
last_name: Schütte
- first_name: Frank
full_name: Noé, Frank
last_name: Noé
citation:
ama: Klus S, Nüske F, Koltai P, et al. Data-Driven Model Reduction and Transfer
Operator Approximation. Journal of Nonlinear Science. 2018:985-1010. doi:10.1007/s00332-017-9437-7
apa: Klus, S., Nüske, F., Koltai, P., Wu, H., Kevrekidis, I., Schütte, C., &
Noé, F. (2018). Data-Driven Model Reduction and Transfer Operator Approximation.
Journal of Nonlinear Science, 985–1010. https://doi.org/10.1007/s00332-017-9437-7
bibtex: '@article{Klus_Nüske_Koltai_Wu_Kevrekidis_Schütte_Noé_2018, title={Data-Driven
Model Reduction and Transfer Operator Approximation}, DOI={10.1007/s00332-017-9437-7},
journal={Journal of Nonlinear Science}, author={Klus, Stefan and Nüske, Feliks
and Koltai, Péter and Wu, Hao and Kevrekidis, Ioannis and Schütte, Christof and
Noé, Frank}, year={2018}, pages={985–1010} }'
chicago: Klus, Stefan, Feliks Nüske, Péter Koltai, Hao Wu, Ioannis Kevrekidis, Christof
Schütte, and Frank Noé. “Data-Driven Model Reduction and Transfer Operator Approximation.”
Journal of Nonlinear Science, 2018, 985–1010. https://doi.org/10.1007/s00332-017-9437-7.
ieee: S. Klus et al., “Data-Driven Model Reduction and Transfer Operator
Approximation,” Journal of Nonlinear Science, pp. 985–1010, 2018.
mla: Klus, Stefan, et al. “Data-Driven Model Reduction and Transfer Operator Approximation.”
Journal of Nonlinear Science, 2018, pp. 985–1010, doi:10.1007/s00332-017-9437-7.
short: S. Klus, F. Nüske, P. Koltai, H. Wu, I. Kevrekidis, C. Schütte, F. Noé, Journal
of Nonlinear Science (2018) 985–1010.
date_created: 2021-04-30T16:59:03Z
date_updated: 2022-01-06T06:55:20Z
department:
- _id: '101'
doi: 10.1007/s00332-017-9437-7
extern: '1'
language:
- iso: eng
page: 985-1010
publication: Journal of Nonlinear Science
publication_identifier:
issn:
- 0938-8974
- 1432-1467
publication_status: published
status: public
title: Data-Driven Model Reduction and Transfer Operator Approximation
type: journal_article
user_id: '81513'
year: '2018'
...
---
_id: '21942'
article_number: '241723'
author:
- first_name: Lorenzo
full_name: Boninsegna, Lorenzo
last_name: Boninsegna
- first_name: Feliks
full_name: Nüske, Feliks
id: '81513'
last_name: Nüske
orcid: 0000-0003-2444-7889
- first_name: Cecilia
full_name: Clementi, Cecilia
last_name: Clementi
citation:
ama: Boninsegna L, Nüske F, Clementi C. Sparse learning of stochastic dynamical
equations. The Journal of Chemical Physics. 2018. doi:10.1063/1.5018409
apa: Boninsegna, L., Nüske, F., & Clementi, C. (2018). Sparse learning of stochastic
dynamical equations. The Journal of Chemical Physics. https://doi.org/10.1063/1.5018409
bibtex: '@article{Boninsegna_Nüske_Clementi_2018, title={Sparse learning of stochastic
dynamical equations}, DOI={10.1063/1.5018409},
number={241723}, journal={The Journal of Chemical Physics}, author={Boninsegna,
Lorenzo and Nüske, Feliks and Clementi, Cecilia}, year={2018} }'
chicago: Boninsegna, Lorenzo, Feliks Nüske, and Cecilia Clementi. “Sparse Learning
of Stochastic Dynamical Equations.” The Journal of Chemical Physics, 2018.
https://doi.org/10.1063/1.5018409.
ieee: L. Boninsegna, F. Nüske, and C. Clementi, “Sparse learning of stochastic dynamical
equations,” The Journal of Chemical Physics, 2018.
mla: Boninsegna, Lorenzo, et al. “Sparse Learning of Stochastic Dynamical Equations.”
The Journal of Chemical Physics, 241723, 2018, doi:10.1063/1.5018409.
short: L. Boninsegna, F. Nüske, C. Clementi, The Journal of Chemical Physics (2018).
date_created: 2021-04-30T16:59:39Z
date_updated: 2022-01-06T06:55:20Z
department:
- _id: '101'
doi: 10.1063/1.5018409
extern: '1'
language:
- iso: eng
publication: The Journal of Chemical Physics
publication_identifier:
issn:
- 0021-9606
- 1089-7690
publication_status: published
status: public
title: Sparse learning of stochastic dynamical equations
type: journal_article
user_id: '81513'
year: '2018'
...
---
_id: '21943'
article_number: '244119'
author:
- first_name: Eugen
full_name: Hruska, Eugen
last_name: Hruska
- first_name: Jayvee R.
full_name: Abella, Jayvee R.
last_name: Abella
- first_name: Feliks
full_name: Nüske, Feliks
id: '81513'
last_name: Nüske
orcid: 0000-0003-2444-7889
- first_name: Lydia E.
full_name: Kavraki, Lydia E.
last_name: Kavraki
- first_name: Cecilia
full_name: Clementi, Cecilia
last_name: Clementi
citation:
ama: Hruska E, Abella JR, Nüske F, Kavraki LE, Clementi C. Quantitative comparison
of adaptive sampling methods for protein dynamics. The Journal of Chemical
Physics. 2018. doi:10.1063/1.5053582
apa: Hruska, E., Abella, J. R., Nüske, F., Kavraki, L. E., & Clementi, C. (2018).
Quantitative comparison of adaptive sampling methods for protein dynamics. The
Journal of Chemical Physics. https://doi.org/10.1063/1.5053582
bibtex: '@article{Hruska_Abella_Nüske_Kavraki_Clementi_2018, title={Quantitative
comparison of adaptive sampling methods for protein dynamics}, DOI={10.1063/1.5053582},
number={244119}, journal={The Journal of Chemical Physics}, author={Hruska, Eugen
and Abella, Jayvee R. and Nüske, Feliks and Kavraki, Lydia E. and Clementi, Cecilia},
year={2018} }'
chicago: Hruska, Eugen, Jayvee R. Abella, Feliks Nüske, Lydia E. Kavraki, and Cecilia
Clementi. “Quantitative Comparison of Adaptive Sampling Methods for Protein Dynamics.”
The Journal of Chemical Physics, 2018. https://doi.org/10.1063/1.5053582.
ieee: E. Hruska, J. R. Abella, F. Nüske, L. E. Kavraki, and C. Clementi, “Quantitative
comparison of adaptive sampling methods for protein dynamics,” The Journal
of Chemical Physics, 2018.
mla: Hruska, Eugen, et al. “Quantitative Comparison of Adaptive Sampling Methods
for Protein Dynamics.” The Journal of Chemical Physics, 244119, 2018, doi:10.1063/1.5053582.
short: E. Hruska, J.R. Abella, F. Nüske, L.E. Kavraki, C. Clementi, The Journal
of Chemical Physics (2018).
date_created: 2021-04-30T17:00:24Z
date_updated: 2022-01-06T06:55:20Z
department:
- _id: '101'
doi: 10.1063/1.5053582
extern: '1'
language:
- iso: eng
publication: The Journal of Chemical Physics
publication_identifier:
issn:
- 0021-9606
- 1089-7690
publication_status: published
status: public
title: Quantitative comparison of adaptive sampling methods for protein dynamics
type: journal_article
user_id: '81513'
year: '2018'
...
---
_id: '8750'
abstract:
- lang: eng
text: In this article we propose a descent method for equality and inequality constrained
multiobjective optimization problems (MOPs) which generalizes the steepest descent
method for unconstrained MOPs by Fliege and Svaiter to constrained problems by
using two active set strategies. Under some regularity assumptions on the problem,
we show that accumulation points of our descent method satisfy a necessary condition
for local Pareto optimality. Finally, we show the typical behavior of our method
in a numerical example.
author:
- first_name: Bennet
full_name: Gebken, Bennet
id: '32643'
last_name: Gebken
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
citation:
ama: 'Gebken B, Peitz S, Dellnitz M. A Descent Method for Equality and Inequality
Constrained Multiobjective Optimization Problems. In: Numerical and Evolutionary
Optimization – NEO 2017. Cham; 2018. doi:10.1007/978-3-319-96104-0_2'
apa: Gebken, B., Peitz, S., & Dellnitz, M. (2018). A Descent Method for Equality
and Inequality Constrained Multiobjective Optimization Problems. In Numerical
and Evolutionary Optimization – NEO 2017. Cham. https://doi.org/10.1007/978-3-319-96104-0_2
bibtex: '@inproceedings{Gebken_Peitz_Dellnitz_2018, place={Cham}, title={A Descent
Method for Equality and Inequality Constrained Multiobjective Optimization Problems},
DOI={10.1007/978-3-319-96104-0_2},
booktitle={Numerical and Evolutionary Optimization – NEO 2017}, author={Gebken,
Bennet and Peitz, Sebastian and Dellnitz, Michael}, year={2018} }'
chicago: Gebken, Bennet, Sebastian Peitz, and Michael Dellnitz. “A Descent Method
for Equality and Inequality Constrained Multiobjective Optimization Problems.”
In Numerical and Evolutionary Optimization – NEO 2017. Cham, 2018. https://doi.org/10.1007/978-3-319-96104-0_2.
ieee: B. Gebken, S. Peitz, and M. Dellnitz, “A Descent Method for Equality and Inequality
Constrained Multiobjective Optimization Problems,” in Numerical and Evolutionary
Optimization – NEO 2017, 2018.
mla: Gebken, Bennet, et al. “A Descent Method for Equality and Inequality Constrained
Multiobjective Optimization Problems.” Numerical and Evolutionary Optimization
– NEO 2017, 2018, doi:10.1007/978-3-319-96104-0_2.
short: 'B. Gebken, S. Peitz, M. Dellnitz, in: Numerical and Evolutionary Optimization
– NEO 2017, Cham, 2018.'
conference:
name: 'NEO 2017: Numerical and Evolutionary Optimization'
date_created: 2019-03-29T13:26:47Z
date_updated: 2022-01-06T07:04:00Z
department:
- _id: '101'
doi: 10.1007/978-3-319-96104-0_2
language:
- iso: eng
place: Cham
publication: Numerical and Evolutionary Optimization – NEO 2017
publication_identifier:
isbn:
- '9783319961033'
- '9783319961040'
issn:
- 1860-949X
- 1860-9503
publication_status: published
status: public
title: A Descent Method for Equality and Inequality Constrained Multiobjective Optimization
Problems
type: conference
user_id: '47427'
year: '2018'
...
---
_id: '8751'
abstract:
- lang: eng
text: Multiobjective optimization plays an increasingly important role in modern
applications, where several criteria are often of equal importance. The task in
multiobjective optimization and multiobjective optimal control is therefore to
compute the set of optimal compromises (the Pareto set) between the conflicting
objectives. The advances in algorithms and the increasing interest in Pareto-optimal
solutions have led to a wide range of new applications related to optimal and
feedback control, which results in new challenges such as expensive models or
real-time applicability. Since the Pareto set generally consists of an infinite
number of solutions, the computational effort can quickly become challenging,
which is particularly problematic when the objectives are costly to evaluate or
when a solution has to be presented very quickly. This article gives an overview
of recent developments in accelerating multiobjective optimal control for complex
problems where either PDE constraints are present or where a feedback behavior
has to be achieved. In the first case, surrogate models yield significant speed-ups.
Besides classical meta-modeling techniques for multiobjective optimization, a
promising alternative for control problems is to introduce a surrogate model for
the system dynamics. In the case of real-time requirements, various promising
model predictive control approaches have been proposed, using either fast online
solvers or offline-online decomposition. We also briefly comment on dimension
reduction in many-objective optimization problems as another technique for reducing
the numerical effort.
article_type: review
author:
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
citation:
ama: Peitz S, Dellnitz M. A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate
Models, Feedback Control and Objective Reduction. Mathematical and Computational
Applications. 2018;23(2). doi:10.3390/mca23020030
apa: Peitz, S., & Dellnitz, M. (2018). A Survey of Recent Trends in Multiobjective
Optimal Control—Surrogate Models, Feedback Control and Objective Reduction. Mathematical
and Computational Applications, 23(2). https://doi.org/10.3390/mca23020030
bibtex: '@article{Peitz_Dellnitz_2018, title={A Survey of Recent Trends in Multiobjective
Optimal Control—Surrogate Models, Feedback Control and Objective Reduction}, volume={23},
DOI={10.3390/mca23020030}, number={2},
journal={Mathematical and Computational Applications}, author={Peitz, Sebastian
and Dellnitz, Michael}, year={2018} }'
chicago: Peitz, Sebastian, and Michael Dellnitz. “A Survey of Recent Trends in Multiobjective
Optimal Control—Surrogate Models, Feedback Control and Objective Reduction.” Mathematical
and Computational Applications 23, no. 2 (2018). https://doi.org/10.3390/mca23020030.
ieee: S. Peitz and M. Dellnitz, “A Survey of Recent Trends in Multiobjective Optimal
Control—Surrogate Models, Feedback Control and Objective Reduction,” Mathematical
and Computational Applications, vol. 23, no. 2, 2018.
mla: Peitz, Sebastian, and Michael Dellnitz. “A Survey of Recent Trends in Multiobjective
Optimal Control—Surrogate Models, Feedback Control and Objective Reduction.” Mathematical
and Computational Applications, vol. 23, no. 2, 2018, doi:10.3390/mca23020030.
short: S. Peitz, M. Dellnitz, Mathematical and Computational Applications 23 (2018).
date_created: 2019-03-29T13:27:51Z
date_updated: 2022-01-06T07:04:00Z
department:
- _id: '101'
doi: 10.3390/mca23020030
intvolume: ' 23'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/2297-8747/23/2/30/pdf
oa: '1'
publication: Mathematical and Computational Applications
publication_identifier:
issn:
- 2297-8747
publication_status: published
status: public
title: A Survey of Recent Trends in Multiobjective Optimal Control—Surrogate Models,
Feedback Control and Objective Reduction
type: journal_article
user_id: '47427'
volume: 23
year: '2018'
...
---
_id: '8754'
abstract:
- lang: eng
text: In this chapter, we combine a global, derivative-free subdivision algorithm
for multiobjective optimization problems with a posteriori error estimates for
reduced-order models based on Proper Orthogonal Decomposition in order to efficiently
solve multiobjective optimization problems governed by partial differential equations.
An error bound for a semilinear heat equation is developed in such a way that
the errors in the conflicting objectives can be estimated individually. The resulting
algorithm constructs a library of locally valid reduced-order models online using
a Greedy (worst-first) search. Using this approach, the number of evaluations
of the full-order model can be reduced by a factor of more than 1000.
author:
- first_name: Dennis
full_name: Beermann, Dennis
last_name: Beermann
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Stefan
full_name: Volkwein, Stefan
last_name: Volkwein
citation:
ama: 'Beermann D, Dellnitz M, Peitz S, Volkwein S. Set-Oriented Multiobjective Optimal
Control of PDEs Using Proper Orthogonal Decomposition. In: Reduced-Order Modeling
(ROM) for Simulation and Optimization. Cham; 2018:47-72. doi:10.1007/978-3-319-75319-5_3'
apa: Beermann, D., Dellnitz, M., Peitz, S., & Volkwein, S. (2018). Set-Oriented
Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition.
In Reduced-Order Modeling (ROM) for Simulation and Optimization (pp. 47–72).
Cham. https://doi.org/10.1007/978-3-319-75319-5_3
bibtex: '@inbook{Beermann_Dellnitz_Peitz_Volkwein_2018, place={Cham}, title={Set-Oriented
Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition},
DOI={10.1007/978-3-319-75319-5_3},
booktitle={Reduced-Order Modeling (ROM) for Simulation and Optimization}, author={Beermann,
Dennis and Dellnitz, Michael and Peitz, Sebastian and Volkwein, Stefan}, year={2018},
pages={47–72} }'
chicago: Beermann, Dennis, Michael Dellnitz, Sebastian Peitz, and Stefan Volkwein.
“Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal Decomposition.”
In Reduced-Order Modeling (ROM) for Simulation and Optimization, 47–72.
Cham, 2018. https://doi.org/10.1007/978-3-319-75319-5_3.
ieee: D. Beermann, M. Dellnitz, S. Peitz, and S. Volkwein, “Set-Oriented Multiobjective
Optimal Control of PDEs Using Proper Orthogonal Decomposition,” in Reduced-Order
Modeling (ROM) for Simulation and Optimization, Cham, 2018, pp. 47–72.
mla: Beermann, Dennis, et al. “Set-Oriented Multiobjective Optimal Control of PDEs
Using Proper Orthogonal Decomposition.” Reduced-Order Modeling (ROM) for Simulation
and Optimization, 2018, pp. 47–72, doi:10.1007/978-3-319-75319-5_3.
short: 'D. Beermann, M. Dellnitz, S. Peitz, S. Volkwein, in: Reduced-Order Modeling
(ROM) for Simulation and Optimization, Cham, 2018, pp. 47–72.'
date_created: 2019-03-29T13:31:20Z
date_updated: 2022-01-06T07:04:00Z
department:
- _id: '101'
doi: 10.1007/978-3-319-75319-5_3
language:
- iso: eng
page: 47-72
place: Cham
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Reduced-Order Modeling (ROM) for Simulation and Optimization
publication_identifier:
isbn:
- '9783319753188'
- '9783319753195'
publication_status: published
status: public
title: Set-Oriented Multiobjective Optimal Control of PDEs Using Proper Orthogonal
Decomposition
type: book_chapter
user_id: '47427'
year: '2018'
...
---
_id: '8755'
abstract:
- lang: eng
text: Dynamic mode decomposition (DMD) is a recently developed tool for the analysis
of the behavior of complex dynamical systems. In this paper, we will propose an
extension of DMD that exploits low-rank tensor decompositions of potentially high-dimensional
data sets to compute the corresponding DMD modes and eigenvalues. The goal is
to reduce the computational complexity and also the amount of memory required
to store the data in order to mitigate the curse of dimensionality. The efficiency
of these tensor-based methods will be illustrated with the aid of several different
fluid dynamics problems such as the von Kármán vortex street and the simulation
of two merging vortices.
article_type: original
author:
- first_name: Stefan
full_name: Klus, Stefan
last_name: Klus
- first_name: Patrick
full_name: Gelß, Patrick
last_name: Gelß
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Christof
full_name: Schütte, Christof
last_name: Schütte
citation:
ama: Klus S, Gelß P, Peitz S, Schütte C. Tensor-based dynamic mode decomposition.
Nonlinearity. 2018;31(7):3359-3380. doi:10.1088/1361-6544/aabc8f
apa: Klus, S., Gelß, P., Peitz, S., & Schütte, C. (2018). Tensor-based dynamic
mode decomposition. Nonlinearity, 31(7), 3359–3380. https://doi.org/10.1088/1361-6544/aabc8f
bibtex: '@article{Klus_Gelß_Peitz_Schütte_2018, title={Tensor-based dynamic mode
decomposition}, volume={31}, DOI={10.1088/1361-6544/aabc8f},
number={7}, journal={Nonlinearity}, author={Klus, Stefan and Gelß, Patrick and
Peitz, Sebastian and Schütte, Christof}, year={2018}, pages={3359–3380} }'
chicago: 'Klus, Stefan, Patrick Gelß, Sebastian Peitz, and Christof Schütte. “Tensor-Based
Dynamic Mode Decomposition.” Nonlinearity 31, no. 7 (2018): 3359–80. https://doi.org/10.1088/1361-6544/aabc8f.'
ieee: S. Klus, P. Gelß, S. Peitz, and C. Schütte, “Tensor-based dynamic mode decomposition,”
Nonlinearity, vol. 31, no. 7, pp. 3359–3380, 2018.
mla: Klus, Stefan, et al. “Tensor-Based Dynamic Mode Decomposition.” Nonlinearity,
vol. 31, no. 7, 2018, pp. 3359–80, doi:10.1088/1361-6544/aabc8f.
short: S. Klus, P. Gelß, S. Peitz, C. Schütte, Nonlinearity 31 (2018) 3359–3380.
date_created: 2019-03-29T13:32:04Z
date_updated: 2022-01-06T07:04:00Z
department:
- _id: '101'
doi: 10.1088/1361-6544/aabc8f
intvolume: ' 31'
issue: '7'
language:
- iso: eng
page: 3359-3380
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Nonlinearity
publication_identifier:
issn:
- 0951-7715
- 1361-6544
publication_status: published
status: public
title: Tensor-based dynamic mode decomposition
type: journal_article
user_id: '47427'
volume: 31
year: '2018'
...
---
_id: '8757'
abstract:
- lang: eng
text: A framework for set‐oriented multiobjective optimal control of partial differential
equations using reduced order modeling has recently been developed [1]. Following
concepts from localized reduced bases methods, error estimators for the reduced
cost functionals are utilized to construct a library of locally valid reduced
order models. This way, a superset of the Pareto set can efficiently be computed
while maintaining a prescribed error bound. In this article, this algorithm is
applied to a problem with non‐smooth objective functionals. Using an academic
example, we show that the extension to non‐smooth problems can be realized in
a straightforward manner. We then discuss the implications on the numerical results.
author:
- first_name: Dennis
full_name: Beermann, Dennis
last_name: Beermann
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Stefan
full_name: Volkwein, Stefan
last_name: Volkwein
citation:
ama: 'Beermann D, Dellnitz M, Peitz S, Volkwein S. POD-based multiobjective optimal
control of PDEs with non-smooth objectives. In: PAMM. ; 2018:51-54. doi:10.1002/pamm.201710015'
apa: Beermann, D., Dellnitz, M., Peitz, S., & Volkwein, S. (2018). POD-based
multiobjective optimal control of PDEs with non-smooth objectives. In PAMM
(pp. 51–54). https://doi.org/10.1002/pamm.201710015
bibtex: '@inproceedings{Beermann_Dellnitz_Peitz_Volkwein_2018, title={POD-based
multiobjective optimal control of PDEs with non-smooth objectives}, DOI={10.1002/pamm.201710015},
booktitle={PAMM}, author={Beermann, Dennis and Dellnitz, Michael and Peitz, Sebastian
and Volkwein, Stefan}, year={2018}, pages={51–54} }'
chicago: Beermann, Dennis, Michael Dellnitz, Sebastian Peitz, and Stefan Volkwein.
“POD-Based Multiobjective Optimal Control of PDEs with Non-Smooth Objectives.”
In PAMM, 51–54, 2018. https://doi.org/10.1002/pamm.201710015.
ieee: D. Beermann, M. Dellnitz, S. Peitz, and S. Volkwein, “POD-based multiobjective
optimal control of PDEs with non-smooth objectives,” in PAMM, 2018, pp.
51–54.
mla: Beermann, Dennis, et al. “POD-Based Multiobjective Optimal Control of PDEs
with Non-Smooth Objectives.” PAMM, 2018, pp. 51–54, doi:10.1002/pamm.201710015.
short: 'D. Beermann, M. Dellnitz, S. Peitz, S. Volkwein, in: PAMM, 2018, pp. 51–54.'
date_created: 2019-03-29T13:34:25Z
date_updated: 2022-01-06T07:04:00Z
department:
- _id: '101'
doi: 10.1002/pamm.201710015
language:
- iso: eng
page: 51-54
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: PAMM
publication_identifier:
issn:
- 1617-7061
publication_status: published
status: public
title: POD-based multiobjective optimal control of PDEs with non-smooth objectives
type: conference
user_id: '47427'
year: '2018'
...
---
_id: '6595'
author:
- first_name: Nadine
full_name: Feldmann, Nadine
id: '23082'
last_name: Feldmann
- first_name: Benjamin
full_name: Jurgelucks, Benjamin
last_name: Jurgelucks
- first_name: Leander
full_name: Claes, Leander
id: '11829'
last_name: Claes
orcid: 0000-0002-4393-268X
- first_name: Bernd
full_name: Henning, Bernd
id: '213'
last_name: Henning
citation:
ama: Feldmann N, Jurgelucks B, Claes L, Henning B. Vollständige Charakterisierung
von Piezoelektrischen Scheiben Mit Ringelektroden. Workshop “Messtechnische
Anwendungen von Ultraschall”, Drübeck; 2018.
apa: Feldmann, N., Jurgelucks, B., Claes, L., & Henning, B. (2018). Vollständige
Charakterisierung von piezoelektrischen Scheiben mit Ringelektroden. Workshop
“Messtechnische Anwendungen von Ultraschall”, Drübeck.
bibtex: '@book{Feldmann_Jurgelucks_Claes_Henning_2018, place={Workshop “Messtechnische
Anwendungen von Ultraschall”, Drübeck}, title={Vollständige Charakterisierung
von piezoelektrischen Scheiben mit Ringelektroden}, author={Feldmann, Nadine and
Jurgelucks, Benjamin and Claes, Leander and Henning, Bernd}, year={2018} }'
chicago: Feldmann, Nadine, Benjamin Jurgelucks, Leander Claes, and Bernd Henning.
Vollständige Charakterisierung von Piezoelektrischen Scheiben Mit Ringelektroden.
Workshop “Messtechnische Anwendungen von Ultraschall”, Drübeck, 2018.
ieee: N. Feldmann, B. Jurgelucks, L. Claes, and B. Henning, Vollständige Charakterisierung
von piezoelektrischen Scheiben mit Ringelektroden. Workshop “Messtechnische
Anwendungen von Ultraschall”, Drübeck, 2018.
mla: Feldmann, Nadine, et al. Vollständige Charakterisierung von Piezoelektrischen
Scheiben Mit Ringelektroden. 2018.
short: N. Feldmann, B. Jurgelucks, L. Claes, B. Henning, Vollständige Charakterisierung
von Piezoelektrischen Scheiben Mit Ringelektroden, Workshop “Messtechnische Anwendungen
von Ultraschall”, Drübeck, 2018.
date_created: 2019-01-09T16:14:18Z
date_updated: 2022-01-06T07:03:13Z
department:
- _id: '49'
- _id: '104'
language:
- iso: eng
place: Workshop "Messtechnische Anwendungen von Ultraschall", Drübeck
project:
- _id: '90'
name: Ein modellbasiertes Messverfahren zur Charakterisierung der frequenzabhängigen
Materialeigenschaften von Piezokeramiken unter Verwendung eines einzelnen Probekörperindividuums
status: public
title: Vollständige Charakterisierung von piezoelektrischen Scheiben mit Ringelektroden
type: misc
user_id: '11829'
year: '2018'
...
---
_id: '16713'
author:
- first_name: Christian
full_name: Gölz, Christian
last_name: Gölz
- first_name: Claudia
full_name: Voelcker-Rehage, Claudia
last_name: Voelcker-Rehage
- first_name: Karin
full_name: Mora, Karin
last_name: Mora
- first_name: Eva-Maria
full_name: Reuter, Eva-Maria
last_name: Reuter
- first_name: Ben
full_name: Godde, Ben
last_name: Godde
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
- first_name: Claus
full_name: Reinsberger, Claus
last_name: Reinsberger
- first_name: Solveig
full_name: Vieluf, Solveig
last_name: Vieluf
citation:
ama: Gölz C, Voelcker-Rehage C, Mora K, et al. Improved Neural Control of Movements
Manifests in Expertise-Related Differences in Force Output and Brain Network Dynamics.
Frontiers in Physiology. 2018. doi:10.3389/fphys.2018.01540
apa: Gölz, C., Voelcker-Rehage, C., Mora, K., Reuter, E.-M., Godde, B., Dellnitz,
M., … Vieluf, S. (2018). Improved Neural Control of Movements Manifests in Expertise-Related
Differences in Force Output and Brain Network Dynamics. Frontiers in Physiology.
https://doi.org/10.3389/fphys.2018.01540
bibtex: '@article{Gölz_Voelcker-Rehage_Mora_Reuter_Godde_Dellnitz_Reinsberger_Vieluf_2018,
title={Improved Neural Control of Movements Manifests in Expertise-Related Differences
in Force Output and Brain Network Dynamics}, DOI={10.3389/fphys.2018.01540},
journal={Frontiers in Physiology}, author={Gölz, Christian and Voelcker-Rehage,
Claudia and Mora, Karin and Reuter, Eva-Maria and Godde, Ben and Dellnitz, Michael
and Reinsberger, Claus and Vieluf, Solveig}, year={2018} }'
chicago: Gölz, Christian, Claudia Voelcker-Rehage, Karin Mora, Eva-Maria Reuter,
Ben Godde, Michael Dellnitz, Claus Reinsberger, and Solveig Vieluf. “Improved
Neural Control of Movements Manifests in Expertise-Related Differences in Force
Output and Brain Network Dynamics.” Frontiers in Physiology, 2018. https://doi.org/10.3389/fphys.2018.01540.
ieee: C. Gölz et al., “Improved Neural Control of Movements Manifests in
Expertise-Related Differences in Force Output and Brain Network Dynamics,” Frontiers
in Physiology, 2018.
mla: Gölz, Christian, et al. “Improved Neural Control of Movements Manifests in
Expertise-Related Differences in Force Output and Brain Network Dynamics.” Frontiers
in Physiology, 2018, doi:10.3389/fphys.2018.01540.
short: C. Gölz, C. Voelcker-Rehage, K. Mora, E.-M. Reuter, B. Godde, M. Dellnitz,
C. Reinsberger, S. Vieluf, Frontiers in Physiology (2018).
date_created: 2020-04-16T14:08:06Z
date_updated: 2022-01-06T06:52:55Z
department:
- _id: '101'
doi: 10.3389/fphys.2018.01540
language:
- iso: eng
publication: Frontiers in Physiology
publication_identifier:
issn:
- 1664-042X
publication_status: published
status: public
title: Improved Neural Control of Movements Manifests in Expertise-Related Differences
in Force Output and Brain Network Dynamics
type: journal_article
user_id: '47427'
year: '2018'
...
---
_id: '16714'
author:
- first_name: Solveig
full_name: Vieluf, Solveig
last_name: Vieluf
- first_name: Karin
full_name: Mora, Karin
last_name: Mora
- first_name: Christian
full_name: Gölz, Christian
last_name: Gölz
- first_name: Eva-Maria
full_name: Reuter, Eva-Maria
last_name: Reuter
- first_name: Ben
full_name: Godde, Ben
last_name: Godde
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
- first_name: Claus
full_name: Reinsberger, Claus
last_name: Reinsberger
- first_name: Claudia
full_name: Voelcker-Rehage, Claudia
last_name: Voelcker-Rehage
citation:
ama: Vieluf S, Mora K, Gölz C, et al. Age- and Expertise-Related Differences of
Sensorimotor Network Dynamics during Force Control. Neuroscience. 2018:203-213.
doi:10.1016/j.neuroscience.2018.07.025
apa: Vieluf, S., Mora, K., Gölz, C., Reuter, E.-M., Godde, B., Dellnitz, M., … Voelcker-Rehage,
C. (2018). Age- and Expertise-Related Differences of Sensorimotor Network Dynamics
during Force Control. Neuroscience, 203–213. https://doi.org/10.1016/j.neuroscience.2018.07.025
bibtex: '@article{Vieluf_Mora_Gölz_Reuter_Godde_Dellnitz_Reinsberger_Voelcker-Rehage_2018,
title={Age- and Expertise-Related Differences of Sensorimotor Network Dynamics
during Force Control}, DOI={10.1016/j.neuroscience.2018.07.025},
journal={Neuroscience}, author={Vieluf, Solveig and Mora, Karin and Gölz, Christian
and Reuter, Eva-Maria and Godde, Ben and Dellnitz, Michael and Reinsberger, Claus
and Voelcker-Rehage, Claudia}, year={2018}, pages={203–213} }'
chicago: Vieluf, Solveig, Karin Mora, Christian Gölz, Eva-Maria Reuter, Ben Godde,
Michael Dellnitz, Claus Reinsberger, and Claudia Voelcker-Rehage. “Age- and Expertise-Related
Differences of Sensorimotor Network Dynamics during Force Control.” Neuroscience,
2018, 203–13. https://doi.org/10.1016/j.neuroscience.2018.07.025.
ieee: S. Vieluf et al., “Age- and Expertise-Related Differences of Sensorimotor
Network Dynamics during Force Control,” Neuroscience, pp. 203–213, 2018.
mla: Vieluf, Solveig, et al. “Age- and Expertise-Related Differences of Sensorimotor
Network Dynamics during Force Control.” Neuroscience, 2018, pp. 203–13,
doi:10.1016/j.neuroscience.2018.07.025.
short: S. Vieluf, K. Mora, C. Gölz, E.-M. Reuter, B. Godde, M. Dellnitz, C. Reinsberger,
C. Voelcker-Rehage, Neuroscience (2018) 203–213.
date_created: 2020-04-16T14:08:51Z
date_updated: 2022-01-06T06:52:55Z
department:
- _id: '101'
doi: 10.1016/j.neuroscience.2018.07.025
language:
- iso: eng
page: 203-213
publication: Neuroscience
publication_identifier:
issn:
- 0306-4522
publication_status: published
status: public
title: Age- and Expertise-Related Differences of Sensorimotor Network Dynamics during
Force Control
type: journal_article
user_id: '47427'
year: '2018'
...
---
_id: '16715'
author:
- first_name: Andreas
full_name: Bittracher, Andreas
last_name: Bittracher
- first_name: Péter
full_name: Koltai, Péter
last_name: Koltai
- first_name: Stefan
full_name: Klus, Stefan
last_name: Klus
- first_name: Ralf
full_name: Banisch, Ralf
last_name: Banisch
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
- first_name: Christof
full_name: Schütte, Christof
last_name: Schütte
citation:
ama: Bittracher A, Koltai P, Klus S, Banisch R, Dellnitz M, Schütte C. Transition
Manifolds of Complex Metastable Systems. Journal of Nonlinear Science.
2018;28:471-512. doi:10.1007/s00332-017-9415-0
apa: Bittracher, A., Koltai, P., Klus, S., Banisch, R., Dellnitz, M., & Schütte,
C. (2018). Transition Manifolds of Complex Metastable Systems. Journal of Nonlinear
Science, 28, 471–512. https://doi.org/10.1007/s00332-017-9415-0
bibtex: '@article{Bittracher_Koltai_Klus_Banisch_Dellnitz_Schütte_2018, title={Transition
Manifolds of Complex Metastable Systems}, volume={28}, DOI={10.1007/s00332-017-9415-0},
journal={Journal of Nonlinear Science}, author={Bittracher, Andreas and Koltai,
Péter and Klus, Stefan and Banisch, Ralf and Dellnitz, Michael and Schütte, Christof},
year={2018}, pages={471–512} }'
chicago: 'Bittracher, Andreas, Péter Koltai, Stefan Klus, Ralf Banisch, Michael
Dellnitz, and Christof Schütte. “Transition Manifolds of Complex Metastable Systems.”
Journal of Nonlinear Science 28 (2018): 471–512. https://doi.org/10.1007/s00332-017-9415-0.'
ieee: A. Bittracher, P. Koltai, S. Klus, R. Banisch, M. Dellnitz, and C. Schütte,
“Transition Manifolds of Complex Metastable Systems,” Journal of Nonlinear
Science, vol. 28, pp. 471–512, 2018.
mla: Bittracher, Andreas, et al. “Transition Manifolds of Complex Metastable Systems.”
Journal of Nonlinear Science, vol. 28, 2018, pp. 471–512, doi:10.1007/s00332-017-9415-0.
short: A. Bittracher, P. Koltai, S. Klus, R. Banisch, M. Dellnitz, C. Schütte, Journal
of Nonlinear Science 28 (2018) 471–512.
date_created: 2020-04-16T14:09:31Z
date_updated: 2022-01-06T06:52:55Z
department:
- _id: '101'
doi: 10.1007/s00332-017-9415-0
intvolume: ' 28'
language:
- iso: eng
page: 471-512
publication: Journal of Nonlinear Science
publication_identifier:
issn:
- 0938-8974
- 1432-1467
publication_status: published
status: public
title: Transition Manifolds of Complex Metastable Systems
type: journal_article
user_id: '47427'
volume: 28
year: '2018'
...
---
_id: '16292'
abstract:
- lang: eng
text: "In a recent article, we presented a framework to control nonlinear partial\r\ndifferential
equations (PDEs) by means of Koopman operator based reduced models\r\nand concepts
from switched systems. The main idea was to transform a control\r\nsystem into
a set of autonomous systems for which the optimal switching\r\nsequence has to
be computed. These individual systems can be approximated very\r\nefficiently
by reduced order models obtained from data, and one can guarantee\r\nequality
of the full and the reduced objective function under certain\r\nassumptions. In
this article, we extend these results to continuous control\r\ninputs using convex
combinations of multiple Koopman operators corresponding to\r\nconstant controls,
which results in a bilinear control system. Although\r\nequality of the objectives
can be carried over when the PDE depends linearly on\r\nthe control, we show that
this approach is also valid in other scenarios using\r\nseveral flow control examples
of varying complexity."
author:
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
citation:
ama: Peitz S. Controlling nonlinear PDEs using low-dimensional bilinear approximations
obtained from data. arXiv:180106419. 2018.
apa: Peitz, S. (2018). Controlling nonlinear PDEs using low-dimensional bilinear
approximations obtained from data. ArXiv:1801.06419.
bibtex: '@article{Peitz_2018, title={Controlling nonlinear PDEs using low-dimensional
bilinear approximations obtained from data}, journal={arXiv:1801.06419}, author={Peitz,
Sebastian}, year={2018} }'
chicago: Peitz, Sebastian. “Controlling Nonlinear PDEs Using Low-Dimensional Bilinear
Approximations Obtained from Data.” ArXiv:1801.06419, 2018.
ieee: S. Peitz, “Controlling nonlinear PDEs using low-dimensional bilinear approximations
obtained from data,” arXiv:1801.06419. 2018.
mla: Peitz, Sebastian. “Controlling Nonlinear PDEs Using Low-Dimensional Bilinear
Approximations Obtained from Data.” ArXiv:1801.06419, 2018.
short: S. Peitz, ArXiv:1801.06419 (2018).
date_created: 2020-03-13T12:43:14Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '101'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/1801.06419.pdf
oa: '1'
publication: arXiv:1801.06419
status: public
title: Controlling nonlinear PDEs using low-dimensional bilinear approximations obtained
from data
type: preprint
user_id: '47427'
year: '2018'
...
---
_id: '16293'
abstract:
- lang: eng
text: "Kernel transfer operators, which can be regarded as approximations of\r\ntransfer
operators such as the Perron-Frobenius or Koopman operator in\r\nreproducing kernel
Hilbert spaces, are defined in terms of covariance and\r\ncross-covariance operators
and have been shown to be closely related to the\r\nconditional mean embedding
framework developed by the machine learning\r\ncommunity. The goal of this paper
is to show how the dominant eigenfunctions of\r\nthese operators in combination
with gradient-based optimization techniques can\r\nbe used to detect long-lived
coherent patterns in high-dimensional time-series\r\ndata. The results will be
illustrated using video data and a fluid flow\r\nexample."
author:
- first_name: Stefan
full_name: Klus, Stefan
last_name: Klus
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Ingmar
full_name: Schuster, Ingmar
last_name: Schuster
citation:
ama: Klus S, Peitz S, Schuster I. Analyzing high-dimensional time-series data using
kernel transfer operator eigenfunctions. arXiv:180510118. 2018.
apa: Klus, S., Peitz, S., & Schuster, I. (2018). Analyzing high-dimensional
time-series data using kernel transfer operator eigenfunctions. ArXiv:1805.10118.
bibtex: '@article{Klus_Peitz_Schuster_2018, title={Analyzing high-dimensional time-series
data using kernel transfer operator eigenfunctions}, journal={arXiv:1805.10118},
author={Klus, Stefan and Peitz, Sebastian and Schuster, Ingmar}, year={2018} }'
chicago: Klus, Stefan, Sebastian Peitz, and Ingmar Schuster. “Analyzing High-Dimensional
Time-Series Data Using Kernel Transfer Operator Eigenfunctions.” ArXiv:1805.10118,
2018.
ieee: S. Klus, S. Peitz, and I. Schuster, “Analyzing high-dimensional time-series
data using kernel transfer operator eigenfunctions,” arXiv:1805.10118.
2018.
mla: Klus, Stefan, et al. “Analyzing High-Dimensional Time-Series Data Using Kernel
Transfer Operator Eigenfunctions.” ArXiv:1805.10118, 2018.
short: S. Klus, S. Peitz, I. Schuster, ArXiv:1805.10118 (2018).
date_created: 2020-03-13T12:44:12Z
date_updated: 2022-01-06T06:52:48Z
department:
- _id: '101'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/1805.10118.pdf
oa: '1'
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: arXiv:1805.10118
status: public
title: Analyzing high-dimensional time-series data using kernel transfer operator
eigenfunctions
type: preprint
user_id: '47427'
year: '2018'
...
---
_id: '10129'
abstract:
- lang: eng
text: There are many hard conjectures in graph theory, like Tutte's 5-flow conjecture,
and the 5-cycle double cover conjecture, which would be true in general if they
would be true for cubic graphs. Since most of them are trivially true for 3-edge-colorable
cubic graphs, cubic graphs which are not 3-edge-colorable, often called snarks,
play a key role in this context. Here, we survey parameters measuring how far
apart a non 3-edge-colorable graph is from being 3-edge-colorable. We study their
interrelation and prove some new results. Besides getting new insight into the
structure of snarks, we show that such measures give partial results with respect
to these important conjectures. The paper closes with a list of open problems
and conjectures.
article_number: P4.54
article_type: original
author:
- first_name: M. A.
full_name: Fiol, M. A.
last_name: Fiol
- first_name: Guiseppe
full_name: Mazzuoccolo, Guiseppe
last_name: Mazzuoccolo
- first_name: Eckhard
full_name: Steffen, Eckhard
id: '15548'
last_name: Steffen
citation:
ama: Fiol MA, Mazzuoccolo G, Steffen E. Measures of Edge-Uncolorability of Cubic
Graphs. The Electronic Journal of Combinatorics. 2018;25(4).
apa: Fiol, M. A., Mazzuoccolo, G., & Steffen, E. (2018). Measures of Edge-Uncolorability
of Cubic Graphs. The Electronic Journal of Combinatorics, 25(4).
bibtex: '@article{Fiol_Mazzuoccolo_Steffen_2018, title={Measures of Edge-Uncolorability
of Cubic Graphs}, volume={25}, number={4P4.54}, journal={The Electronic Journal
of Combinatorics}, author={Fiol, M. A. and Mazzuoccolo, Guiseppe and Steffen,
Eckhard}, year={2018} }'
chicago: Fiol, M. A., Guiseppe Mazzuoccolo, and Eckhard Steffen. “Measures of Edge-Uncolorability
of Cubic Graphs.” The Electronic Journal of Combinatorics 25, no. 4 (2018).
ieee: M. A. Fiol, G. Mazzuoccolo, and E. Steffen, “Measures of Edge-Uncolorability
of Cubic Graphs,” The Electronic Journal of Combinatorics, vol. 25, no.
4, 2018.
mla: Fiol, M. A., et al. “Measures of Edge-Uncolorability of Cubic Graphs.” The
Electronic Journal of Combinatorics, vol. 25, no. 4, P4.54, 2018.
short: M.A. Fiol, G. Mazzuoccolo, E. Steffen, The Electronic Journal of Combinatorics
25 (2018).
date_created: 2019-06-05T09:59:10Z
date_updated: 2022-01-06T06:50:30Z
department:
- _id: '542'
intvolume: ' 25'
issue: '4'
keyword:
- Cubic graph
- Tait coloring
- Snark
- Boole coloring
- Berge's conjecture
- Tutte's 5-flow conjecture
language:
- iso: eng
publication: The Electronic Journal of Combinatorics
status: public
title: Measures of Edge-Uncolorability of Cubic Graphs
type: journal_article
user_id: '15540'
volume: 25
year: '2018'
...
---
_id: '10132'
author:
- first_name: Ligang
full_name: Jin, Ligang
last_name: Jin
- first_name: Giuseppe
full_name: Mazzuoccolo, Giuseppe
last_name: Mazzuoccolo
- first_name: Eckhard
full_name: Steffen, Eckhard
id: '15548'
last_name: Steffen
citation:
ama: Jin L, Mazzuoccolo G, Steffen E. Cores, joins and the Fano-flow conjectures.
Discussiones Mathematicae Graph Theory. 2018;38:165-175. doi:10.7151/dmgt.1999
apa: Jin, L., Mazzuoccolo, G., & Steffen, E. (2018). Cores, joins and the Fano-flow
conjectures. Discussiones Mathematicae Graph Theory, 38, 165–175.
https://doi.org/10.7151/dmgt.1999
bibtex: '@article{Jin_Mazzuoccolo_Steffen_2018, title={Cores, joins and the Fano-flow
conjectures}, volume={38}, DOI={10.7151/dmgt.1999},
journal={Discussiones Mathematicae Graph Theory}, author={Jin, Ligang and Mazzuoccolo,
Giuseppe and Steffen, Eckhard}, year={2018}, pages={165–175} }'
chicago: 'Jin, Ligang, Giuseppe Mazzuoccolo, and Eckhard Steffen. “Cores, Joins
and the Fano-Flow Conjectures.” Discussiones Mathematicae Graph Theory
38 (2018): 165–75. https://doi.org/10.7151/dmgt.1999.'
ieee: L. Jin, G. Mazzuoccolo, and E. Steffen, “Cores, joins and the Fano-flow conjectures,”
Discussiones Mathematicae Graph Theory, vol. 38, pp. 165–175, 2018.
mla: Jin, Ligang, et al. “Cores, Joins and the Fano-Flow Conjectures.” Discussiones
Mathematicae Graph Theory, vol. 38, 2018, pp. 165–75, doi:10.7151/dmgt.1999.
short: L. Jin, G. Mazzuoccolo, E. Steffen, Discussiones Mathematicae Graph Theory
38 (2018) 165–175.
date_created: 2019-06-05T10:08:41Z
date_updated: 2022-01-06T06:50:30Z
department:
- _id: '542'
doi: 10.7151/dmgt.1999
intvolume: ' 38'
language:
- iso: eng
page: 165-175
publication: Discussiones Mathematicae Graph Theory
publication_identifier:
issn:
- 1234-3099
- 2083-5892
publication_status: published
status: public
title: Cores, joins and the Fano-flow conjectures
type: journal_article
user_id: '15540'
volume: 38
year: '2018'
...
---
_id: '10142'
author:
- first_name: Eckhard
full_name: Steffen, Eckhard
id: '15548'
last_name: Steffen
citation:
ama: Steffen E. Approximating Vizing’s independence number conjecture. Australasian
Journal of Combinatorics. 2018;71(1):153-160.
apa: Steffen, E. (2018). Approximating Vizing’s independence number conjecture.
Australasian Journal of Combinatorics, 71(1), 153–160.
bibtex: '@article{Steffen_2018, title={Approximating Vizing’s independence number
conjecture}, volume={71}, number={1}, journal={Australasian Journal of Combinatorics},
author={Steffen, Eckhard}, year={2018}, pages={153–160} }'
chicago: 'Steffen, Eckhard. “Approximating Vizing’s Independence Number Conjecture.”
Australasian Journal of Combinatorics 71, no. 1 (2018): 153–60.'
ieee: E. Steffen, “Approximating Vizing’s independence number conjecture,” Australasian
Journal of Combinatorics, vol. 71, no. 1, pp. 153–160, 2018.
mla: Steffen, Eckhard. “Approximating Vizing’s Independence Number Conjecture.”
Australasian Journal of Combinatorics, vol. 71, no. 1, 2018, pp. 153–60.
short: E. Steffen, Australasian Journal of Combinatorics 71 (2018) 153–160.
date_created: 2019-06-07T08:36:36Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '542'
intvolume: ' 71'
issue: '1'
language:
- iso: eng
page: 153-160
publication: Australasian Journal of Combinatorics
publication_status: published
status: public
title: Approximating Vizing’s independence number conjecture
type: journal_article
user_id: '15540'
volume: 71
year: '2018'
...
---
_id: '8753'
abstract:
- lang: eng
text: In a wide range of applications it is desirable to optimally control a dynamical
system with respect to concurrent, potentially competing goals. This gives rise
to a multiobjective optimal control problem where, instead of computing a single
optimal solution, the set of optimal compromises, the so-called Pareto set, has
to be approximated. When the problem under consideration is described by a partial
differential equation (PDE), as is the case for fluid flow, the computational
cost rapidly increases and makes its direct treatment infeasible. Reduced order
modeling is a very popular method to reduce the computational cost, in particular
in a multi query context such as uncertainty quantification, parameter estimation
or optimization. In this article, we show how to combine reduced order modeling
and multiobjective optimal control techniques in order to efficiently solve multiobjective
optimal control problems constrained by PDEs. We consider a global, derivative
free optimization method as well as a local, gradient-based approach for which
the optimality system is derived in two different ways. The methods are compared
with regard to the solution quality as well as the computational effort and they
are illustrated using the example of the flow around a cylinder and a backward-facing-step
channel flow.
author:
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Sina
full_name: Ober-Blöbaum, Sina
id: '16494'
last_name: Ober-Blöbaum
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
citation:
ama: Peitz S, Ober-Blöbaum S, Dellnitz M. Multiobjective Optimal Control Methods
for the Navier-Stokes Equations Using Reduced Order Modeling. Acta Applicandae
Mathematicae. 2018;161(1):171–199. doi:10.1007/s10440-018-0209-7
apa: Peitz, S., Ober-Blöbaum, S., & Dellnitz, M. (2018). Multiobjective Optimal
Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling.
Acta Applicandae Mathematicae, 161(1), 171–199. https://doi.org/10.1007/s10440-018-0209-7
bibtex: '@article{Peitz_Ober-Blöbaum_Dellnitz_2018, title={Multiobjective Optimal
Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling},
volume={161}, DOI={10.1007/s10440-018-0209-7},
number={1}, journal={Acta Applicandae Mathematicae}, author={Peitz, Sebastian
and Ober-Blöbaum, Sina and Dellnitz, Michael}, year={2018}, pages={171–199} }'
chicago: 'Peitz, Sebastian, Sina Ober-Blöbaum, and Michael Dellnitz. “Multiobjective
Optimal Control Methods for the Navier-Stokes Equations Using Reduced Order Modeling.”
Acta Applicandae Mathematicae 161, no. 1 (2018): 171–199. https://doi.org/10.1007/s10440-018-0209-7.'
ieee: 'S. Peitz, S. Ober-Blöbaum, and M. Dellnitz, “Multiobjective Optimal Control
Methods for the Navier-Stokes Equations Using Reduced Order Modeling,” Acta
Applicandae Mathematicae, vol. 161, no. 1, pp. 171–199, 2018, doi: 10.1007/s10440-018-0209-7.'
mla: Peitz, Sebastian, et al. “Multiobjective Optimal Control Methods for the Navier-Stokes
Equations Using Reduced Order Modeling.” Acta Applicandae Mathematicae,
vol. 161, no. 1, 2018, pp. 171–199, doi:10.1007/s10440-018-0209-7.
short: S. Peitz, S. Ober-Blöbaum, M. Dellnitz, Acta Applicandae Mathematicae 161
(2018) 171–199.
date_created: 2019-03-29T13:30:41Z
date_updated: 2022-01-21T10:01:41Z
department:
- _id: '101'
doi: 10.1007/s10440-018-0209-7
intvolume: ' 161'
issue: '1'
language:
- iso: eng
page: 171–199
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Acta Applicandae Mathematicae
publication_identifier:
issn:
- 0167-8019
- 1572-9036
publication_status: published
status: public
title: Multiobjective Optimal Control Methods for the Navier-Stokes Equations Using
Reduced Order Modeling
type: journal_article
user_id: '15694'
volume: 161
year: '2018'
...
---
_id: '29425'
author:
- first_name: F.
full_name: Jiménez, F.
last_name: Jiménez
- first_name: Sina
full_name: Ober-Blöbaum, Sina
id: '16494'
last_name: Ober-Blöbaum
citation:
ama: 'Jiménez F, Ober-Blöbaum S. Necessary optimality conditions for optimally controlled
dissipative mechanical systems modelled through fractional derivatives. In: 6th
European Conference on Computational Mechanics. ; 2018.'
apa: Jiménez, F., & Ober-Blöbaum, S. (2018). Necessary optimality conditions
for optimally controlled dissipative mechanical systems modelled through fractional
derivatives. 6th European Conference on Computational Mechanics.
bibtex: '@inproceedings{Jiménez_Ober-Blöbaum_2018, title={Necessary optimality conditions
for optimally controlled dissipative mechanical systems modelled through fractional
derivatives}, booktitle={6th European Conference on Computational Mechanics},
author={Jiménez, F. and Ober-Blöbaum, Sina}, year={2018} }'
chicago: Jiménez, F., and Sina Ober-Blöbaum. “Necessary Optimality Conditions for
Optimally Controlled Dissipative Mechanical Systems Modelled through Fractional
Derivatives.” In 6th European Conference on Computational Mechanics, 2018.
ieee: F. Jiménez and S. Ober-Blöbaum, “Necessary optimality conditions for optimally
controlled dissipative mechanical systems modelled through fractional derivatives,”
2018.
mla: Jiménez, F., and Sina Ober-Blöbaum. “Necessary Optimality Conditions for Optimally
Controlled Dissipative Mechanical Systems Modelled through Fractional Derivatives.”
6th European Conference on Computational Mechanics, 2018.
short: 'F. Jiménez, S. Ober-Blöbaum, in: 6th European Conference on Computational
Mechanics, 2018.'
conference:
end_date: 2018-06-15
start_date: 2018-06-11
date_created: 2022-01-18T14:49:40Z
date_updated: 2022-01-21T13:51:41Z
department:
- _id: '636'
language:
- iso: eng
publication: 6th European Conference on Computational Mechanics
status: public
title: Necessary optimality conditions for optimally controlled dissipative mechanical
systems modelled through fractional derivatives
type: conference
user_id: '15694'
year: '2018'
...