---
_id: '63800'
abstract:
- lang: eng
text: In this contribution, we address the estimation of the frequency-dependent
elastic parameters of polymers in the ultrasound range, which is formulated as
an inverse problem. This inverse problem is implemented as a nonlinear regression-type
optimization problem, in which the simulation signals are fitted to the measurement
signals. These signals consist of displacement responses in waveguides, focusing
on hollow cylindrical geometries to enhance the simulation efficiency. To accelerate
the optimization and reduce the number of model evaluations and wait times, we
propose two novel methods. First, we introduce an adaptation of the Levenberg–Marquardt
method derived from a geometrical interpretation of the least-squares optimization
problem. Second, we introduce an improved objective function based on the autocorrelated
envelopes of the measurement and simulation signals. Given that this study primarily
relies on simulation data to quantify optimization convergence, we aggregate the
expected ranges of realistic material parameters and derive their distributions
to ensure the reproducibility of optimizations with proper measurements. We demonstrate
the effectiveness of our objective function modification and step adaptation for
various materials with isotropic material symmetry by comparing them with the
Broyden–Fletcher–Goldfarb–Shanno method. In all cases, our method reduces the
total number of model evaluations, thereby shortening the time to identify the
material parameters.
author:
- first_name: Dominik
full_name: Itner, Dominik
last_name: Itner
- first_name: Dmitrij
full_name: Dreiling, Dmitrij
id: '32616'
last_name: Dreiling
- first_name: Hauke
full_name: Gravenkamp, Hauke
last_name: Gravenkamp
- first_name: Bernd
full_name: Henning, Bernd
id: '213'
last_name: Henning
- first_name: Carolin
full_name: Birk, Carolin
last_name: Birk
citation:
ama: Itner D, Dreiling D, Gravenkamp H, Henning B, Birk C. A modified Levenberg–Marquardt
method for estimating the elastic material parameters of polymer waveguides using
residuals between autocorrelated frequency responses. Mechanical Systems and
Signal Processing. 2026;247:113904. doi:https://doi.org/10.1016/j.ymssp.2026.113904
apa: Itner, D., Dreiling, D., Gravenkamp, H., Henning, B., & Birk, C. (2026).
A modified Levenberg–Marquardt method for estimating the elastic material parameters
of polymer waveguides using residuals between autocorrelated frequency responses.
Mechanical Systems and Signal Processing, 247, 113904. https://doi.org/10.1016/j.ymssp.2026.113904
bibtex: '@article{Itner_Dreiling_Gravenkamp_Henning_Birk_2026, title={A modified
Levenberg–Marquardt method for estimating the elastic material parameters of polymer
waveguides using residuals between autocorrelated frequency responses}, volume={247},
DOI={https://doi.org/10.1016/j.ymssp.2026.113904},
journal={Mechanical Systems and Signal Processing}, author={Itner, Dominik and
Dreiling, Dmitrij and Gravenkamp, Hauke and Henning, Bernd and Birk, Carolin},
year={2026}, pages={113904} }'
chicago: 'Itner, Dominik, Dmitrij Dreiling, Hauke Gravenkamp, Bernd Henning, and
Carolin Birk. “A Modified Levenberg–Marquardt Method for Estimating the Elastic
Material Parameters of Polymer Waveguides Using Residuals between Autocorrelated
Frequency Responses.” Mechanical Systems and Signal Processing 247 (2026):
113904. https://doi.org/10.1016/j.ymssp.2026.113904.'
ieee: 'D. Itner, D. Dreiling, H. Gravenkamp, B. Henning, and C. Birk, “A modified
Levenberg–Marquardt method for estimating the elastic material parameters of polymer
waveguides using residuals between autocorrelated frequency responses,” Mechanical
Systems and Signal Processing, vol. 247, p. 113904, 2026, doi: https://doi.org/10.1016/j.ymssp.2026.113904.'
mla: Itner, Dominik, et al. “A Modified Levenberg–Marquardt Method for Estimating
the Elastic Material Parameters of Polymer Waveguides Using Residuals between
Autocorrelated Frequency Responses.” Mechanical Systems and Signal Processing,
vol. 247, 2026, p. 113904, doi:https://doi.org/10.1016/j.ymssp.2026.113904.
short: D. Itner, D. Dreiling, H. Gravenkamp, B. Henning, C. Birk, Mechanical Systems
and Signal Processing 247 (2026) 113904.
date_created: 2026-01-29T08:53:42Z
date_updated: 2026-02-02T12:44:47Z
department:
- _id: '49'
doi: https://doi.org/10.1016/j.ymssp.2026.113904
intvolume: ' 247'
keyword:
- Material parameter estimation
- Waveguide
- Nonlinear optimization
- Inverse problem
- Least squares
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.sciencedirect.com/science/article/pii/S0888327026000610/pdfft?md5=16e8493b44527f4ab0a6d13f634a01c3&pid=1-s2.0-S0888327026000610-main.pdf
oa: '1'
page: '113904'
project:
- _id: '89'
name: Vollständige Bestimmung der akustischen Materialparameter von Polymeren
publication: Mechanical Systems and Signal Processing
publication_identifier:
issn:
- 0888-3270
publication_status: published
status: public
title: A modified Levenberg–Marquardt method for estimating the elastic material parameters
of polymer waveguides using residuals between autocorrelated frequency responses
type: journal_article
user_id: '32616'
volume: 247
year: '2026'
...
---
_id: '57472'
abstract:
- lang: eng
text: In this paper we introduce, in a Hilbert space setting, a second order dynamical
system with asymptotically vanishing damping and vanishing Tikhonov regularization
that approaches a multiobjective optimization problem with convex and differentiable
components of the objective function. Trajectory solutions are shown to exist
in finite dimensions. We prove fast convergence of the function values, quantified
in terms of a merit function. Based on the regime considered, we establish both
weak and, in some cases, strong convergence of trajectory solutions toward a weak
Pareto optimal solution. To achieve this, we apply Tikhonov regularization individually
to each component of the objective function. This work extends results from single
objective convex optimization into the multiobjective setting.
author:
- first_name: Radu Ioan
full_name: Bot, Radu Ioan
last_name: Bot
- first_name: Konstantin
full_name: Sonntag, Konstantin
id: '56399'
last_name: Sonntag
orcid: https://orcid.org/0000-0003-3384-3496
citation:
ama: Bot RI, Sonntag K. Inertial dynamics with vanishing Tikhonov regularization
for multobjective optimization. Journal of Mathematical Analysis and Applications.
Published online 2025.
apa: Bot, R. I., & Sonntag, K. (2025). Inertial dynamics with vanishing Tikhonov
regularization for multobjective optimization. Journal of Mathematical Analysis
and Applications.
bibtex: '@article{Bot_Sonntag_2025, title={Inertial dynamics with vanishing Tikhonov
regularization for multobjective optimization}, journal={Journal of Mathematical
Analysis and Applications}, author={Bot, Radu Ioan and Sonntag, Konstantin}, year={2025}
}'
chicago: Bot, Radu Ioan, and Konstantin Sonntag. “Inertial Dynamics with Vanishing
Tikhonov Regularization for Multobjective Optimization.” Journal of Mathematical
Analysis and Applications, 2025.
ieee: R. I. Bot and K. Sonntag, “Inertial dynamics with vanishing Tikhonov regularization
for multobjective optimization,” Journal of Mathematical Analysis and Applications,
2025.
mla: Bot, Radu Ioan, and Konstantin Sonntag. “Inertial Dynamics with Vanishing Tikhonov
Regularization for Multobjective Optimization.” Journal of Mathematical Analysis
and Applications, 2025.
short: R.I. Bot, K. Sonntag, Journal of Mathematical Analysis and Applications (2025).
date_created: 2024-11-28T08:58:17Z
date_updated: 2025-10-16T11:56:36Z
ddc:
- '510'
department:
- _id: '101'
- _id: '530'
- _id: '655'
external_id:
arxiv:
- '2411.18422'
file:
- access_level: open_access
content_type: application/pdf
creator: sonntagk
date_created: 2024-11-28T08:58:00Z
date_updated: 2024-11-28T08:58:00Z
file_id: '57473'
file_name: Inertial dynamics with vanishing Tikhonov regularization for multobjective
optimization.pdf
file_size: 4291134
relation: main_file
file_date_updated: 2024-11-28T08:58:00Z
has_accepted_license: '1'
keyword:
- Pareto optimization
- Lyapunov analysis
- gradient-like dynamical systems
- inertial dynamics
- asymptotic vanishing damping
- Tikhonov regularization
- strong convergence
language:
- iso: eng
main_file_link:
- url: https://arxiv.org/pdf/2411.18422
oa: '1'
publication: Journal of Mathematical Analysis and Applications
status: public
title: Inertial dynamics with vanishing Tikhonov regularization for multobjective
optimization
type: journal_article
user_id: '56399'
year: '2025'
...
---
_id: '63053'
author:
- first_name: Carlos
full_name: Hernández, Carlos
last_name: Hernández
- first_name: Angel E.
full_name: Rodriguez-Fernandez, Angel E.
last_name: Rodriguez-Fernandez
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Oliver
full_name: Cuate, Oliver
last_name: Cuate
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Oliver
full_name: Schütze, Oliver
last_name: Schütze
citation:
ama: Hernández C, Rodriguez-Fernandez AE, Schäpermeier L, Cuate O, Trautmann H,
Schütze O. An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions
for Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary
Computation. Published online 2025:1-1. doi:10.1109/TEVC.2025.3637276
apa: Hernández, C., Rodriguez-Fernandez, A. E., Schäpermeier, L., Cuate, O., Trautmann,
H., & Schütze, O. (2025). An Evolutionary Approach for the Computation of
∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. IEEE
Transactions on Evolutionary Computation, 1–1. https://doi.org/10.1109/TEVC.2025.3637276
bibtex: '@article{Hernández_Rodriguez-Fernandez_Schäpermeier_Cuate_Trautmann_Schütze_2025,
title={An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions
for Multi-Objective Multimodal Optimization}, DOI={10.1109/TEVC.2025.3637276},
journal={IEEE Transactions on Evolutionary Computation}, author={Hernández, Carlos
and Rodriguez-Fernandez, Angel E. and Schäpermeier, Lennart and Cuate, Oliver
and Trautmann, Heike and Schütze, Oliver}, year={2025}, pages={1–1} }'
chicago: Hernández, Carlos, Angel E. Rodriguez-Fernandez, Lennart Schäpermeier,
Oliver Cuate, Heike Trautmann, and Oliver Schütze. “An Evolutionary Approach for
the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal
Optimization.” IEEE Transactions on Evolutionary Computation, 2025, 1–1.
https://doi.org/10.1109/TEVC.2025.3637276.
ieee: 'C. Hernández, A. E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann,
and O. Schütze, “An Evolutionary Approach for the Computation of ∈-Locally Optimal
Solutions for Multi-Objective Multimodal Optimization,” IEEE Transactions on
Evolutionary Computation, pp. 1–1, 2025, doi: 10.1109/TEVC.2025.3637276.'
mla: Hernández, Carlos, et al. “An Evolutionary Approach for the Computation of
∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” IEEE
Transactions on Evolutionary Computation, 2025, pp. 1–1, doi:10.1109/TEVC.2025.3637276.
short: C. Hernández, A.E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann,
O. Schütze, IEEE Transactions on Evolutionary Computation (2025) 1–1.
date_created: 2025-12-12T06:13:06Z
date_updated: 2025-12-12T06:13:51Z
department:
- _id: '819'
doi: 10.1109/TEVC.2025.3637276
keyword:
- Optimization
- Evolutionary computation
- Hands
- Proposals
- Convergence
- Computational efficiency
- Artificial intelligence
- Accuracy
- Approximation algorithms
- Aerospace electronics
- Multi-objective optimization
- evolutionary algorithms
- nearly optimal solutions
- multimodal optimization
- archiving
- continuation
language:
- iso: eng
page: 1-1
publication: IEEE Transactions on Evolutionary Computation
status: public
title: An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions
for Multi-Objective Multimodal Optimization
type: journal_article
user_id: '15504'
year: '2025'
...
---
_id: '51208'
abstract:
- lang: eng
text: AbstractApproximation of subdifferentials
is one of the main tasks when computing descent directions for nonsmooth optimization
problems. In this article, we propose a bisection method for weakly lower semismooth
functions which is able to compute new subgradients that improve a given approximation
in case a direction with insufficient descent was computed. Combined with a recently
proposed deterministic gradient sampling approach, this yields a deterministic
and provably convergent way to approximate subdifferentials for computing descent
directions.
author:
- first_name: Bennet
full_name: Gebken, Bennet
id: '32643'
last_name: Gebken
citation:
ama: Gebken B. A note on the convergence of deterministic gradient sampling in nonsmooth
optimization. Computational Optimization and Applications. Published online
2024. doi:10.1007/s10589-024-00552-0
apa: Gebken, B. (2024). A note on the convergence of deterministic gradient sampling
in nonsmooth optimization. Computational Optimization and Applications.
https://doi.org/10.1007/s10589-024-00552-0
bibtex: '@article{Gebken_2024, title={A note on the convergence of deterministic
gradient sampling in nonsmooth optimization}, DOI={10.1007/s10589-024-00552-0},
journal={Computational Optimization and Applications}, publisher={Springer Science
and Business Media LLC}, author={Gebken, Bennet}, year={2024} }'
chicago: Gebken, Bennet. “A Note on the Convergence of Deterministic Gradient Sampling
in Nonsmooth Optimization.” Computational Optimization and Applications,
2024. https://doi.org/10.1007/s10589-024-00552-0.
ieee: 'B. Gebken, “A note on the convergence of deterministic gradient sampling
in nonsmooth optimization,” Computational Optimization and Applications,
2024, doi: 10.1007/s10589-024-00552-0.'
mla: Gebken, Bennet. “A Note on the Convergence of Deterministic Gradient Sampling
in Nonsmooth Optimization.” Computational Optimization and Applications,
Springer Science and Business Media LLC, 2024, doi:10.1007/s10589-024-00552-0.
short: B. Gebken, Computational Optimization and Applications (2024).
date_created: 2024-02-07T07:23:23Z
date_updated: 2024-02-08T08:05:54Z
department:
- _id: '101'
doi: 10.1007/s10589-024-00552-0
keyword:
- Applied Mathematics
- Computational Mathematics
- Control and Optimization
language:
- iso: eng
publication: Computational Optimization and Applications
publication_identifier:
issn:
- 0926-6003
- 1573-2894
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: A note on the convergence of deterministic gradient sampling in nonsmooth optimization
type: journal_article
user_id: '32643'
year: '2024'
...
---
_id: '52726'
abstract:
- lang: eng
text: Heteroclinic structures organize global features of dynamical systems. We
analyse whether heteroclinic structures can arise in network dynamics with higher-order
interactions which describe the nonlinear interactions between three or more units.
We find that while commonly analysed model equations such as network dynamics
on undirected hypergraphs may be useful to describe local dynamics such as cluster
synchronization, they give rise to obstructions that allow to design of heteroclinic
structures in phase space. By contrast, directed hypergraphs break the homogeneity
and lead to vector fields that support heteroclinic structures.
article_type: original
author:
- first_name: Christian
full_name: Bick, Christian
last_name: Bick
- first_name: Sören
full_name: von der Gracht, Sören
id: '97359'
last_name: von der Gracht
orcid: 0000-0002-8054-2058
citation:
ama: Bick C, von der Gracht S. Heteroclinic dynamics in network dynamical systems
with higher-order interactions. Journal of Complex Networks. 2024;12(2).
doi:10.1093/comnet/cnae009
apa: Bick, C., & von der Gracht, S. (2024). Heteroclinic dynamics in network
dynamical systems with higher-order interactions. Journal of Complex Networks,
12(2). https://doi.org/10.1093/comnet/cnae009
bibtex: '@article{Bick_von der Gracht_2024, title={Heteroclinic dynamics in network
dynamical systems with higher-order interactions}, volume={12}, DOI={10.1093/comnet/cnae009},
number={2}, journal={Journal of Complex Networks}, publisher={Oxford University
Press (OUP)}, author={Bick, Christian and von der Gracht, Sören}, year={2024}
}'
chicago: Bick, Christian, and Sören von der Gracht. “Heteroclinic Dynamics in Network
Dynamical Systems with Higher-Order Interactions.” Journal of Complex Networks
12, no. 2 (2024). https://doi.org/10.1093/comnet/cnae009.
ieee: 'C. Bick and S. von der Gracht, “Heteroclinic dynamics in network dynamical
systems with higher-order interactions,” Journal of Complex Networks, vol.
12, no. 2, 2024, doi: 10.1093/comnet/cnae009.'
mla: Bick, Christian, and Sören von der Gracht. “Heteroclinic Dynamics in Network
Dynamical Systems with Higher-Order Interactions.” Journal of Complex Networks,
vol. 12, no. 2, Oxford University Press (OUP), 2024, doi:10.1093/comnet/cnae009.
short: C. Bick, S. von der Gracht, Journal of Complex Networks 12 (2024).
date_created: 2024-03-22T09:04:57Z
date_updated: 2024-03-22T09:11:53Z
ddc:
- '510'
department:
- _id: '101'
doi: 10.1093/comnet/cnae009
external_id:
arxiv:
- '2309.02006'
file:
- access_level: closed
content_type: application/pdf
creator: svdg
date_created: 2024-03-22T09:06:07Z
date_updated: 2024-03-22T09:06:07Z
file_id: '52728'
file_name: heteroclinic-dynamics-in-network-dynamical-systems-with-higher-order-interactions.pdf
file_size: 649155
relation: main_file
success: 1
file_date_updated: 2024-03-22T09:06:07Z
has_accepted_license: '1'
intvolume: ' 12'
issue: '2'
keyword:
- Applied Mathematics
- Computational Mathematics
- Control and Optimization
- Management Science and Operations Research
- Computer Networks and Communications
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://academic.oup.com/comnet/article-pdf/12/2/cnae009/56832119/cnae009.pdf
oa: '1'
publication: Journal of Complex Networks
publication_identifier:
issn:
- 2051-1329
publication_status: published
publisher: Oxford University Press (OUP)
status: public
title: Heteroclinic dynamics in network dynamical systems with higher-order interactions
type: journal_article
user_id: '97359'
volume: 12
year: '2024'
...
---
_id: '54548'
author:
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: Prager RP, Trautmann H. Exploratory Landscape Analysis for Mixed-Variable Problems.
IEEE Transactions on Evolutionary Computation. Published online 2024:1-1.
doi:10.1109/TEVC.2024.3399560
apa: Prager, R. P., & Trautmann, H. (2024). Exploratory Landscape Analysis for
Mixed-Variable Problems. IEEE Transactions on Evolutionary Computation,
1–1. https://doi.org/10.1109/TEVC.2024.3399560
bibtex: '@article{Prager_Trautmann_2024, title={Exploratory Landscape Analysis for
Mixed-Variable Problems}, DOI={10.1109/TEVC.2024.3399560},
journal={IEEE Transactions on Evolutionary Computation}, author={Prager, Raphael
Patrick and Trautmann, Heike}, year={2024}, pages={1–1} }'
chicago: Prager, Raphael Patrick, and Heike Trautmann. “Exploratory Landscape Analysis
for Mixed-Variable Problems.” IEEE Transactions on Evolutionary Computation,
2024, 1–1. https://doi.org/10.1109/TEVC.2024.3399560.
ieee: 'R. P. Prager and H. Trautmann, “Exploratory Landscape Analysis for Mixed-Variable
Problems,” IEEE Transactions on Evolutionary Computation, pp. 1–1, 2024,
doi: 10.1109/TEVC.2024.3399560.'
mla: Prager, Raphael Patrick, and Heike Trautmann. “Exploratory Landscape Analysis
for Mixed-Variable Problems.” IEEE Transactions on Evolutionary Computation,
2024, pp. 1–1, doi:10.1109/TEVC.2024.3399560.
short: R.P. Prager, H. Trautmann, IEEE Transactions on Evolutionary Computation
(2024) 1–1.
date_created: 2024-06-03T06:16:33Z
date_updated: 2024-06-03T06:17:13Z
department:
- _id: '819'
doi: 10.1109/TEVC.2024.3399560
keyword:
- Optimization
- Evolutionary computation
- Benchmark testing
- Hyperparameter optimization
- Portfolios
- Extraterrestrial measurements
- Dispersion
- Exploratory landscape analysis
- mixed-variable problem
- mixed search spaces
- automated algorithm selection
language:
- iso: eng
page: 1-1
publication: IEEE Transactions on Evolutionary Computation
status: public
title: Exploratory Landscape Analysis for Mixed-Variable Problems
type: journal_article
user_id: '15504'
year: '2024'
...
---
_id: '32447'
abstract:
- lang: eng
text: 'We present a new gradient-like dynamical system related to unconstrained
convex smooth multiobjective optimization which involves inertial effects and
asymptotic vanishing damping. To the best of our knowledge, this system is the
first inertial gradient-like system for multiobjective optimization problems including
asymptotic vanishing damping, expanding the ideas previously laid out in [H. Attouch
and G. Garrigos, Multiobjective Optimization: An Inertial Dynamical Approach to
Pareto Optima, preprint, arXiv:1506.02823, 2015]. We prove existence of solutions
to this system in finite dimensions and further prove that its bounded solutions
converge weakly to weakly Pareto optimal points. In addition, we obtain a convergence
rate of order \(\mathcal{O}(t^{-2})\) for the function values measured with a
merit function. This approach presents a good basis for the development of fast
gradient methods for multiobjective optimization.'
article_type: original
author:
- first_name: Konstantin
full_name: Sonntag, Konstantin
id: '56399'
last_name: Sonntag
orcid: https://orcid.org/0000-0003-3384-3496
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: 0000-0002-3389-793X
citation:
ama: Sonntag K, Peitz S. Fast Convergence of Inertial Multiobjective Gradient-Like
Systems with Asymptotic Vanishing Damping. SIAM Journal on Optimization.
2024;34(3):2259-2286. doi:10.1137/23M1588512
apa: Sonntag, K., & Peitz, S. (2024). Fast Convergence of Inertial Multiobjective
Gradient-Like Systems with Asymptotic Vanishing Damping. SIAM Journal on Optimization,
34(3), 2259–2286. https://doi.org/10.1137/23M1588512
bibtex: '@article{Sonntag_Peitz_2024, title={Fast Convergence of Inertial Multiobjective
Gradient-Like Systems with Asymptotic Vanishing Damping}, volume={34}, DOI={10.1137/23M1588512}, number={3},
journal={SIAM Journal on Optimization}, publisher={Society for Industrial and
Applied Mathematics}, author={Sonntag, Konstantin and Peitz, Sebastian}, year={2024},
pages={2259–2286} }'
chicago: 'Sonntag, Konstantin, and Sebastian Peitz. “Fast Convergence of Inertial
Multiobjective Gradient-Like Systems with Asymptotic Vanishing Damping.” SIAM
Journal on Optimization 34, no. 3 (2024): 2259–86. https://doi.org/10.1137/23M1588512.'
ieee: 'K. Sonntag and S. Peitz, “Fast Convergence of Inertial Multiobjective Gradient-Like
Systems with Asymptotic Vanishing Damping,” SIAM Journal on Optimization,
vol. 34, no. 3, pp. 2259–2286, 2024, doi: 10.1137/23M1588512.'
mla: Sonntag, Konstantin, and Sebastian Peitz. “Fast Convergence of Inertial Multiobjective
Gradient-Like Systems with Asymptotic Vanishing Damping.” SIAM Journal on Optimization,
vol. 34, no. 3, Society for Industrial and Applied Mathematics, 2024, pp. 2259–86,
doi:10.1137/23M1588512.
short: K. Sonntag, S. Peitz, SIAM Journal on Optimization 34 (2024) 2259–2286.
date_created: 2022-07-28T11:53:02Z
date_updated: 2024-07-02T09:27:39Z
department:
- _id: '101'
- _id: '655'
doi: 10.1137/23M1588512
intvolume: ' 34'
issue: '3'
keyword:
- multiobjective optimization
- Pareto optimization
- Lyapunov analysis
- gradient-likedynamical systems
- inertial dynamics
- asymptotic vanishing damping
- fast convergence
language:
- iso: eng
page: 2259 - 2286
publication: SIAM Journal on Optimization
publication_identifier:
issn:
- 1095-7189
publication_status: published
publisher: Society for Industrial and Applied Mathematics
status: public
title: Fast Convergence of Inertial Multiobjective Gradient-Like Systems with Asymptotic
Vanishing Damping
type: journal_article
user_id: '56399'
volume: 34
year: '2024'
...
---
_id: '56221'
author:
- first_name: Angel E.
full_name: Rodriguez-Fernandez, Angel E.
last_name: Rodriguez-Fernandez
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Carlos
full_name: Hernández, Carlos
last_name: Hernández
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Oliver
full_name: Schütze, Oliver
last_name: Schütze
citation:
ama: Rodriguez-Fernandez AE, Schäpermeier L, Hernández C, Kerschke P, Trautmann
H, Schütze O. Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal
Optimization. IEEE Transactions on Evolutionary Computation. Published
online 2024:1-1. doi:10.1109/TEVC.2024.3458855
apa: Rodriguez-Fernandez, A. E., Schäpermeier, L., Hernández, C., Kerschke, P.,
Trautmann, H., & Schütze, O. (2024). Finding ϵ-Locally Optimal Solutions for
Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary
Computation, 1–1. https://doi.org/10.1109/TEVC.2024.3458855
bibtex: '@article{Rodriguez-Fernandez_Schäpermeier_Hernández_Kerschke_Trautmann_Schütze_2024,
title={Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization},
DOI={10.1109/TEVC.2024.3458855},
journal={IEEE Transactions on Evolutionary Computation}, author={Rodriguez-Fernandez,
Angel E. and Schäpermeier, Lennart and Hernández, Carlos and Kerschke, Pascal
and Trautmann, Heike and Schütze, Oliver}, year={2024}, pages={1–1} }'
chicago: Rodriguez-Fernandez, Angel E., Lennart Schäpermeier, Carlos Hernández,
Pascal Kerschke, Heike Trautmann, and Oliver Schütze. “Finding ϵ-Locally Optimal
Solutions for Multi-Objective Multimodal Optimization.” IEEE Transactions on
Evolutionary Computation, 2024, 1–1. https://doi.org/10.1109/TEVC.2024.3458855.
ieee: 'A. E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H.
Trautmann, and O. Schütze, “Finding ϵ-Locally Optimal Solutions for Multi-Objective
Multimodal Optimization,” IEEE Transactions on Evolutionary Computation,
pp. 1–1, 2024, doi: 10.1109/TEVC.2024.3458855.'
mla: Rodriguez-Fernandez, Angel E., et al. “Finding ϵ-Locally Optimal Solutions
for Multi-Objective Multimodal Optimization.” IEEE Transactions on Evolutionary
Computation, 2024, pp. 1–1, doi:10.1109/TEVC.2024.3458855.
short: A.E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H.
Trautmann, O. Schütze, IEEE Transactions on Evolutionary Computation (2024) 1–1.
date_created: 2024-09-24T08:01:14Z
date_updated: 2024-09-24T08:01:47Z
doi: 10.1109/TEVC.2024.3458855
keyword:
- Optimization
- Evolutionary computation
- Approximation algorithms
- Benchmark testing
- Vectors
- Surveys
- Pareto optimization
- multi-objective optimization
- evolutionary computation
- multimodal optimization
- local solutions
language:
- iso: eng
page: 1-1
publication: IEEE Transactions on Evolutionary Computation
status: public
title: Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization
type: journal_article
user_id: '15504'
year: '2024'
...
---
_id: '63497'
author:
- first_name: Nikolas
full_name: Förster, Nikolas
last_name: Förster
- first_name: Oliver
full_name: Wallscheid, Oliver
last_name: Wallscheid
- first_name: Frank
full_name: Schafmeister, Frank
last_name: Schafmeister
citation:
ama: 'Förster N, Wallscheid O, Schafmeister F. Dual-Active Bridge Sequential Pareto
Optimization for Fast Pre-Design and Final Component Selection. In: 2024 IEEE
Design Methodologies Conference (DMC). ; 2024:1-8. doi:10.1109/DMC62632.2024.10812131'
apa: Förster, N., Wallscheid, O., & Schafmeister, F. (2024). Dual-Active Bridge
Sequential Pareto Optimization for Fast Pre-Design and Final Component Selection.
2024 IEEE Design Methodologies Conference (DMC), 1–8. https://doi.org/10.1109/DMC62632.2024.10812131
bibtex: '@inproceedings{Förster_Wallscheid_Schafmeister_2024, title={Dual-Active
Bridge Sequential Pareto Optimization for Fast Pre-Design and Final Component
Selection}, DOI={10.1109/DMC62632.2024.10812131},
booktitle={2024 IEEE Design Methodologies Conference (DMC)}, author={Förster,
Nikolas and Wallscheid, Oliver and Schafmeister, Frank}, year={2024}, pages={1–8}
}'
chicago: Förster, Nikolas, Oliver Wallscheid, and Frank Schafmeister. “Dual-Active
Bridge Sequential Pareto Optimization for Fast Pre-Design and Final Component
Selection.” In 2024 IEEE Design Methodologies Conference (DMC), 1–8, 2024.
https://doi.org/10.1109/DMC62632.2024.10812131.
ieee: 'N. Förster, O. Wallscheid, and F. Schafmeister, “Dual-Active Bridge Sequential
Pareto Optimization for Fast Pre-Design and Final Component Selection,” in 2024
IEEE Design Methodologies Conference (DMC), 2024, pp. 1–8, doi: 10.1109/DMC62632.2024.10812131.'
mla: Förster, Nikolas, et al. “Dual-Active Bridge Sequential Pareto Optimization
for Fast Pre-Design and Final Component Selection.” 2024 IEEE Design Methodologies
Conference (DMC), 2024, pp. 1–8, doi:10.1109/DMC62632.2024.10812131.
short: 'N. Förster, O. Wallscheid, F. Schafmeister, in: 2024 IEEE Design Methodologies
Conference (DMC), 2024, pp. 1–8.'
date_created: 2026-01-06T08:06:24Z
date_updated: 2026-01-06T08:07:50Z
department:
- _id: '52'
doi: 10.1109/DMC62632.2024.10812131
keyword:
- MOSFET
- Thermal resistance
- Surface resistance
- Bridge circuits
- Zero voltage switching
- Pareto optimization
- Capacitance
- Numerical simulation
- Optimization
- Resistance heating
- Pareto Optimization
- Dual-Active Bridge
- ZVS
- Inductor Optimization
- Transformer Optimization
- Heat Sink Optimization
language:
- iso: eng
page: 1-8
publication: 2024 IEEE Design Methodologies Conference (DMC)
status: public
title: Dual-Active Bridge Sequential Pareto Optimization for Fast Pre-Design and Final
Component Selection
type: conference
user_id: '83383'
year: '2024'
...
---
_id: '56089'
abstract:
- lang: eng
text: Additive manufacturing (AM) technologies enable near-net-shape designs
and demand-oriented material usage, which significantly minimizes waste. This
points to a substantial opportunity for further optimization in material savings
and process design. The current study delves into the advancement of sustainable
manufacturing practices in the automotive industry, emphasizing the crucial role
of lightweight construction concepts and AM technologies in enhancing resource
efficiency and reducing greenhouse gas emissions. By exploring the integration
of novel AM techniques such as selective laser melting (SLM) and laser metal deposition
(LMD), the study aims to overcome existing limitations like slow build-up rates
and limited component resolution. The study’s core objective revolves around the
development and validation of a continuous process chain that synergizes different
AM routes. In the current study, the continuous process chain for DMG MORI Lasertec
65 3D’s LMD system and the DMG MORI Lasertec 30 3D’s was demonstrated using 316L
and 1.2709 steel materials. This integrated approach is designed to significantly
curtail process times and minimize component costs, thus suggesting an industry-oriented
process chain for future manufacturing paradigms. Additionally, the research investigates
the production and material behavior of components under varying manufacturing
processes, material combinations, and boundary layer materials. The culmination
of this study is the validation of the proposed process route through a technology
demonstrator, assessing its scalability and setting a benchmark for resource-efficient
manufacturing in the automotive sector.
article_number: '772'
article_type: original
author:
- first_name: Deviprasad
full_name: Chalicheemalapalli Jayasankar, Deviprasad
id: '49504'
last_name: Chalicheemalapalli Jayasankar
orcid: https://orcid.org/ 0000-0002-3446-2444
- first_name: Stefan
full_name: Gnaase, Stefan
id: '25730'
last_name: Gnaase
- first_name: Maximilian Alexander
full_name: Kaiser, Maximilian Alexander
id: '72351'
last_name: Kaiser
orcid: 0009-0008-1333-3396
- first_name: Dennis
full_name: Lehnert, Dennis
id: '90491'
last_name: Lehnert
- first_name: Thomas
full_name: Tröster, Thomas
id: '553'
last_name: Tröster
citation:
ama: 'Chalicheemalapalli Jayasankar D, Gnaase S, Kaiser MA, Lehnert D, Tröster T.
Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance
Applications. Metals. 2024;14(7). doi:10.3390/met14070772'
apa: 'Chalicheemalapalli Jayasankar, D., Gnaase, S., Kaiser, M. A., Lehnert, D.,
& Tröster, T. (2024). Advancements in Hybrid Additive Manufacturing: Integrating
SLM and LMD for High-Performance Applications. Metals, 14(7), Article
772. https://doi.org/10.3390/met14070772'
bibtex: '@article{Chalicheemalapalli Jayasankar_Gnaase_Kaiser_Lehnert_Tröster_2024,
title={Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD
for High-Performance Applications}, volume={14}, DOI={10.3390/met14070772},
number={7772}, journal={Metals}, publisher={MDPI AG}, author={Chalicheemalapalli
Jayasankar, Deviprasad and Gnaase, Stefan and Kaiser, Maximilian Alexander and
Lehnert, Dennis and Tröster, Thomas}, year={2024} }'
chicago: 'Chalicheemalapalli Jayasankar, Deviprasad, Stefan Gnaase, Maximilian Alexander
Kaiser, Dennis Lehnert, and Thomas Tröster. “Advancements in Hybrid Additive Manufacturing:
Integrating SLM and LMD for High-Performance Applications.” Metals 14,
no. 7 (2024). https://doi.org/10.3390/met14070772.'
ieee: 'D. Chalicheemalapalli Jayasankar, S. Gnaase, M. A. Kaiser, D. Lehnert, and
T. Tröster, “Advancements in Hybrid Additive Manufacturing: Integrating SLM and
LMD for High-Performance Applications,” Metals, vol. 14, no. 7, Art. no.
772, 2024, doi: 10.3390/met14070772.'
mla: 'Chalicheemalapalli Jayasankar, Deviprasad, et al. “Advancements in Hybrid
Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications.”
Metals, vol. 14, no. 7, 772, MDPI AG, 2024, doi:10.3390/met14070772.'
short: D. Chalicheemalapalli Jayasankar, S. Gnaase, M.A. Kaiser, D. Lehnert, T.
Tröster, Metals 14 (2024).
date_created: 2024-09-10T10:19:32Z
date_updated: 2026-03-20T08:44:23Z
department:
- _id: '9'
- _id: '321'
- _id: '149'
doi: 10.3390/met14070772
intvolume: ' 14'
issue: '7'
keyword:
- additive manufacturing (AM)
- selective laser melting (SLM)
- laser metal deposition (LMD)
- hybrid manufacturing
- process optimization
- 316L
- '1.2709'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/2075-4701/14/7/772
oa: '1'
publication: Metals
publication_identifier:
issn:
- 2075-4701
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: 'Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for
High-Performance Applications'
type: journal_article
user_id: '49504'
volume: 14
year: '2024'
...
---
_id: '47522'
abstract:
- lang: eng
text: Artificial benchmark functions are commonly used in optimization research
because of their ability to rapidly evaluate potential solutions, making them
a preferred substitute for real-world problems. However, these benchmark functions
have faced criticism for their limited resemblance to real-world problems. In
response, recent research has focused on automatically generating new benchmark
functions for areas where established test suites are inadequate. These approaches
have limitations, such as the difficulty of generating new benchmark functions
that exhibit exploratory landscape analysis (ELA) features beyond those of existing
benchmarks.The objective of this work is to develop a method for generating benchmark
functions for single-objective continuous optimization with user-specified structural
properties. Specifically, we aim to demonstrate a proof of concept for a method
that uses an ELA feature vector to specify these properties in advance. To achieve
this, we begin by generating a random sample of decision space variables and objective
values. We then adjust the objective values using CMA-ES until the corresponding
features of our new problem match the predefined ELA features within a specified
threshold. By iteratively transforming the landscape in this way, we ensure that
the resulting function exhibits the desired properties. To create the final function,
we use the resulting point cloud as training data for a simple neural network
that produces a function exhibiting the target ELA features. We demonstrate the
effectiveness of this approach by replicating the existing functions of the well-known
BBOB suite and creating new functions with ELA feature values that are not present
in BBOB.
author:
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Konstantin
full_name: Dietrich, Konstantin
last_name: Dietrich
- first_name: Lennart
full_name: Schneider, Lennart
last_name: Schneider
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Bernd
full_name: Bischl, Bernd
last_name: Bischl
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Olaf
full_name: Mersmann, Olaf
last_name: Mersmann
citation:
ama: 'Prager RP, Dietrich K, Schneider L, et al. Neural Networks as Black-Box Benchmark
Functions Optimized for Exploratory Landscape Features. In: Proceedings of
the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. FOGA
’23. Association for Computing Machinery; 2023:129–139. doi:10.1145/3594805.3607136'
apa: Prager, R. P., Dietrich, K., Schneider, L., Schäpermeier, L., Bischl, B., Kerschke,
P., Trautmann, H., & Mersmann, O. (2023). Neural Networks as Black-Box Benchmark
Functions Optimized for Exploratory Landscape Features. Proceedings of the
17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 129–139.
https://doi.org/10.1145/3594805.3607136
bibtex: '@inproceedings{Prager_Dietrich_Schneider_Schäpermeier_Bischl_Kerschke_Trautmann_Mersmann_2023,
place={New York, NY, USA}, series={FOGA ’23}, title={Neural Networks as Black-Box
Benchmark Functions Optimized for Exploratory Landscape Features}, DOI={10.1145/3594805.3607136},
booktitle={Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic
Algorithms}, publisher={Association for Computing Machinery}, author={Prager,
Raphael Patrick and Dietrich, Konstantin and Schneider, Lennart and Schäpermeier,
Lennart and Bischl, Bernd and Kerschke, Pascal and Trautmann, Heike and Mersmann,
Olaf}, year={2023}, pages={129–139}, collection={FOGA ’23} }'
chicago: 'Prager, Raphael Patrick, Konstantin Dietrich, Lennart Schneider, Lennart
Schäpermeier, Bernd Bischl, Pascal Kerschke, Heike Trautmann, and Olaf Mersmann.
“Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape
Features.” In Proceedings of the 17th ACM/SIGEVO Conference on Foundations
of Genetic Algorithms, 129–139. FOGA ’23. New York, NY, USA: Association for
Computing Machinery, 2023. https://doi.org/10.1145/3594805.3607136.'
ieee: 'R. P. Prager et al., “Neural Networks as Black-Box Benchmark Functions
Optimized for Exploratory Landscape Features,” in Proceedings of the 17th ACM/SIGEVO
Conference on Foundations of Genetic Algorithms, 2023, pp. 129–139, doi: 10.1145/3594805.3607136.'
mla: Prager, Raphael Patrick, et al. “Neural Networks as Black-Box Benchmark Functions
Optimized for Exploratory Landscape Features.” Proceedings of the 17th ACM/SIGEVO
Conference on Foundations of Genetic Algorithms, Association for Computing
Machinery, 2023, pp. 129–139, doi:10.1145/3594805.3607136.
short: 'R.P. Prager, K. Dietrich, L. Schneider, L. Schäpermeier, B. Bischl, P. Kerschke,
H. Trautmann, O. Mersmann, in: Proceedings of the 17th ACM/SIGEVO Conference on
Foundations of Genetic Algorithms, Association for Computing Machinery, New York,
NY, USA, 2023, pp. 129–139.'
date_created: 2023-09-27T15:43:17Z
date_updated: 2023-10-16T12:33:02Z
department:
- _id: '34'
- _id: '819'
doi: 10.1145/3594805.3607136
keyword:
- Benchmarking
- Instance Generator
- Black-Box Continuous Optimization
- Exploratory Landscape Analysis
- Neural Networks
language:
- iso: eng
page: 129–139
place: New York, NY, USA
publication: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic
Algorithms
publication_identifier:
isbn:
- '9798400702020'
publisher: Association for Computing Machinery
series_title: FOGA ’23
status: public
title: Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory
Landscape Features
type: conference
user_id: '15504'
year: '2023'
...
---
_id: '48869'
abstract:
- lang: eng
text: Evolutionary algorithms have been shown to obtain good solutions for complex
optimization problems in static and dynamic environments. It is important to understand
the behaviour of evolutionary algorithms for complex optimization problems that
also involve dynamic and/or stochastic components in a systematic way in order
to further increase their applicability to real-world problems. We investigate
the node weighted traveling salesperson problem (W-TSP), which provides an abstraction
of a wide range of weighted TSP problems, in dynamic settings. In the dynamic
setting of the problem, items that have to be collected as part of a TSP tour
change over time. We first present a dynamic setup for the dynamic W-TSP parameterized
by different types of changes that are applied to the set of items to be collected
when traversing the tour. Our first experimental investigations study the impact
of such changes on resulting optimized tours in order to provide structural insights
of optimization solutions. Afterwards, we investigate simple mutation-based evolutionary
algorithms and study the impact of the mutation operators and the use of populations
with dealing with the dynamic changes to the node weights of the problem.
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Aneta
full_name: Neumann, Aneta
last_name: Neumann
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Bossek J, Neumann A, Neumann F. On the Impact of Basic Mutation Operators
and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling
Salesperson Problem. In: Proceedings of the Genetic and Evolutionary Computation
Conference. GECCO’23. Association for Computing Machinery; 2023:248–256. doi:10.1145/3583131.3590384'
apa: Bossek, J., Neumann, A., & Neumann, F. (2023). On the Impact of Basic Mutation
Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted
Traveling Salesperson Problem. Proceedings of the Genetic and Evolutionary
Computation Conference, 248–256. https://doi.org/10.1145/3583131.3590384
bibtex: '@inproceedings{Bossek_Neumann_Neumann_2023, place={New York, NY, USA},
series={GECCO’23}, title={On the Impact of Basic Mutation Operators and Populations
within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson
Problem}, DOI={10.1145/3583131.3590384},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Neumann,
Aneta and Neumann, Frank}, year={2023}, pages={248–256}, collection={GECCO’23}
}'
chicago: 'Bossek, Jakob, Aneta Neumann, and Frank Neumann. “On the Impact of Basic
Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic
Weighted Traveling Salesperson Problem.” In Proceedings of the Genetic and
Evolutionary Computation Conference, 248–256. GECCO’23. New York, NY, USA:
Association for Computing Machinery, 2023. https://doi.org/10.1145/3583131.3590384.'
ieee: 'J. Bossek, A. Neumann, and F. Neumann, “On the Impact of Basic Mutation Operators
and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling
Salesperson Problem,” in Proceedings of the Genetic and Evolutionary Computation
Conference, 2023, pp. 248–256, doi: 10.1145/3583131.3590384.'
mla: Bossek, Jakob, et al. “On the Impact of Basic Mutation Operators and Populations
within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson
Problem.” Proceedings of the Genetic and Evolutionary Computation Conference,
Association for Computing Machinery, 2023, pp. 248–256, doi:10.1145/3583131.3590384.
short: 'J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, New York, NY, USA,
2023, pp. 248–256.'
date_created: 2023-11-14T15:58:56Z
date_updated: 2023-12-13T10:46:27Z
department:
- _id: '819'
doi: 10.1145/3583131.3590384
extern: '1'
keyword:
- dynamic optimization
- evolutionary algorithms
- re-optimization
- weighted traveling salesperson problem
language:
- iso: eng
page: 248–256
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- '9798400701191'
publisher: Association for Computing Machinery
series_title: GECCO’23
status: public
title: On the Impact of Basic Mutation Operators and Populations within Evolutionary
Algorithms for the Dynamic Weighted Traveling Salesperson Problem
type: conference
user_id: '102979'
year: '2023'
...
---
_id: '53317'
author:
- first_name: Youshan
full_name: Tao, Youshan
last_name: Tao
- first_name: Michael
full_name: Winkler, Michael
last_name: Winkler
citation:
ama: Tao Y, Winkler M. Global smooth solutions in a three-dimensional cross-diffusive
SIS epidemic model with saturated taxis at large densities. Evolution Equations
and Control Theory. 2023;12(6):1676-1687. doi:10.3934/eect.2023031
apa: Tao, Y., & Winkler, M. (2023). Global smooth solutions in a three-dimensional
cross-diffusive SIS epidemic model with saturated taxis at large densities. Evolution
Equations and Control Theory, 12(6), 1676–1687. https://doi.org/10.3934/eect.2023031
bibtex: '@article{Tao_Winkler_2023, title={Global smooth solutions in a three-dimensional
cross-diffusive SIS epidemic model with saturated taxis at large densities}, volume={12},
DOI={10.3934/eect.2023031},
number={6}, journal={Evolution Equations and Control Theory}, publisher={American
Institute of Mathematical Sciences (AIMS)}, author={Tao, Youshan and Winkler,
Michael}, year={2023}, pages={1676–1687} }'
chicago: 'Tao, Youshan, and Michael Winkler. “Global Smooth Solutions in a Three-Dimensional
Cross-Diffusive SIS Epidemic Model with Saturated Taxis at Large Densities.” Evolution
Equations and Control Theory 12, no. 6 (2023): 1676–87. https://doi.org/10.3934/eect.2023031.'
ieee: 'Y. Tao and M. Winkler, “Global smooth solutions in a three-dimensional cross-diffusive
SIS epidemic model with saturated taxis at large densities,” Evolution Equations
and Control Theory, vol. 12, no. 6, pp. 1676–1687, 2023, doi: 10.3934/eect.2023031.'
mla: Tao, Youshan, and Michael Winkler. “Global Smooth Solutions in a Three-Dimensional
Cross-Diffusive SIS Epidemic Model with Saturated Taxis at Large Densities.” Evolution
Equations and Control Theory, vol. 12, no. 6, American Institute of Mathematical
Sciences (AIMS), 2023, pp. 1676–87, doi:10.3934/eect.2023031.
short: Y. Tao, M. Winkler, Evolution Equations and Control Theory 12 (2023) 1676–1687.
date_created: 2024-04-07T12:30:25Z
date_updated: 2024-04-07T12:36:17Z
doi: 10.3934/eect.2023031
intvolume: ' 12'
issue: '6'
keyword:
- Applied Mathematics
- Control and Optimization
- Modeling and Simulation
language:
- iso: eng
page: 1676-1687
publication: Evolution Equations and Control Theory
publication_identifier:
issn:
- 2163-2480
publication_status: published
publisher: American Institute of Mathematical Sciences (AIMS)
status: public
title: Global smooth solutions in a three-dimensional cross-diffusive SIS epidemic
model with saturated taxis at large densities
type: journal_article
user_id: '31496'
volume: 12
year: '2023'
...
---
_id: '30861'
abstract:
- lang: eng
text: AbstractWe consider the problem of maximization
of metabolite production in bacterial cells formulated as a dynamical optimal
control problem (DOCP). According to Pontryagin’s maximum principle, optimal solutions
are concatenations of singular and bang arcs and exhibit the chattering or Fuller
phenomenon, which is problematic for applications. To avoid chattering, we introduce
a reduced model which is still biologically relevant and retains the important
structural features of the original problem. Using a combination of analytical
and numerical methods, we show that the singular arc is dominant in the studied
DOCPs and exhibits the turnpike property. This property
is further used in order to design simple and realistic suboptimal control strategies.
author:
- first_name: Jean-Baptiste
full_name: Caillau, Jean-Baptiste
last_name: Caillau
- first_name: Walid
full_name: Djema, Walid
last_name: Djema
- first_name: Jean-Luc
full_name: Gouzé, Jean-Luc
last_name: Gouzé
- first_name: Sofya
full_name: Maslovskaya, Sofya
id: '87909'
last_name: Maslovskaya
- first_name: Jean-Baptiste
full_name: Pomet, Jean-Baptiste
last_name: Pomet
citation:
ama: Caillau J-B, Djema W, Gouzé J-L, Maslovskaya S, Pomet J-B. Turnpike Property
in Optimal Microbial Metabolite Production. Journal of Optimization Theory
and Applications. Published online 2022. doi:10.1007/s10957-022-02023-0
apa: Caillau, J.-B., Djema, W., Gouzé, J.-L., Maslovskaya, S., & Pomet, J.-B.
(2022). Turnpike Property in Optimal Microbial Metabolite Production. Journal
of Optimization Theory and Applications. https://doi.org/10.1007/s10957-022-02023-0
bibtex: '@article{Caillau_Djema_Gouzé_Maslovskaya_Pomet_2022, title={Turnpike Property
in Optimal Microbial Metabolite Production}, DOI={10.1007/s10957-022-02023-0},
journal={Journal of Optimization Theory and Applications}, publisher={Springer
Science and Business Media LLC}, author={Caillau, Jean-Baptiste and Djema, Walid
and Gouzé, Jean-Luc and Maslovskaya, Sofya and Pomet, Jean-Baptiste}, year={2022}
}'
chicago: Caillau, Jean-Baptiste, Walid Djema, Jean-Luc Gouzé, Sofya Maslovskaya,
and Jean-Baptiste Pomet. “Turnpike Property in Optimal Microbial Metabolite Production.”
Journal of Optimization Theory and Applications, 2022. https://doi.org/10.1007/s10957-022-02023-0.
ieee: 'J.-B. Caillau, W. Djema, J.-L. Gouzé, S. Maslovskaya, and J.-B. Pomet, “Turnpike
Property in Optimal Microbial Metabolite Production,” Journal of Optimization
Theory and Applications, 2022, doi: 10.1007/s10957-022-02023-0.'
mla: Caillau, Jean-Baptiste, et al. “Turnpike Property in Optimal Microbial Metabolite
Production.” Journal of Optimization Theory and Applications, Springer
Science and Business Media LLC, 2022, doi:10.1007/s10957-022-02023-0.
short: J.-B. Caillau, W. Djema, J.-L. Gouzé, S. Maslovskaya, J.-B. Pomet, Journal
of Optimization Theory and Applications (2022).
date_created: 2022-04-08T17:23:13Z
date_updated: 2022-04-08T18:23:02Z
department:
- _id: '636'
doi: 10.1007/s10957-022-02023-0
keyword:
- Applied Mathematics
- Management Science and Operations Research
- Control and Optimization
language:
- iso: eng
publication: Journal of Optimization Theory and Applications
publication_identifier:
issn:
- 0022-3239
- 1573-2878
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Turnpike Property in Optimal Microbial Metabolite Production
type: journal_article
user_id: '87909'
year: '2022'
...
---
_id: '48882'
abstract:
- lang: eng
text: In multimodal multi-objective optimization (MMMOO), the focus is not solely
on convergence in objective space, but rather also on explicitly ensuring diversity
in decision space. We illustrate why commonly used diversity measures are not
entirely appropriate for this task and propose a sophisticated basin-based evaluation
(BBE) method. Also, BBE variants are developed, capturing the anytime behavior
of algorithms. The set of BBE measures is tested by means of an algorithm configuration
study. We show that these new measures also transfer properties of the well-established
hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective
space convergence. Moreover, we advance MMMOO research by providing insights into
the multimodal performance of the considered algorithms. Specifically, algorithms
exploiting local structures are shown to outperform classical evolutionary multi-objective
optimizers regarding the BBE variants and respective trade-off with HV.
author:
- first_name: Jonathan
full_name: Heins, Jonathan
last_name: Heins
- first_name: Jeroen
full_name: Rook, Jeroen
last_name: Rook
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based
Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G,
Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tusar T, eds. Parallel Problem
Solving from Nature (PPSN XVII). Lecture Notes in Computer Science. Springer
International Publishing; 2022:192–206. doi:10.1007/978-3-031-14714-2_14'
apa: 'Heins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J., & Trautmann,
H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization
Problems. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &
T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII) (pp.
192–206). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_14'
bibtex: '@inproceedings{Heins_Rook_Schäpermeier_Kerschke_Bossek_Trautmann_2022,
place={Cham}, series={Lecture Notes in Computer Science}, title={BBE: Basin-Based
Evaluation of Multimodal Multi-objective Optimization Problems}, DOI={10.1007/978-3-031-14714-2_14},
booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer
International Publishing}, author={Heins, Jonathan and Rook, Jeroen and Schäpermeier,
Lennart and Kerschke, Pascal and Bossek, Jakob and Trautmann, Heike}, editor={Rudolph,
Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa,
Gabriela and Tusar, Tea}, year={2022}, pages={192–206}, collection={Lecture Notes
in Computer Science} }'
chicago: 'Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob
Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective
Optimization Problems.” In Parallel Problem Solving from Nature (PPSN XVII),
edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela
Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer
International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_14.'
ieee: 'J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, and H. Trautmann,
“BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems,”
in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 192–206,
doi: 10.1007/978-3-031-14714-2_14.'
mla: 'Heins, Jonathan, et al. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective
Optimization Problems.” Parallel Problem Solving from Nature (PPSN XVII),
edited by Günter Rudolph et al., Springer International Publishing, 2022, pp.
192–206, doi:10.1007/978-3-031-14714-2_14.'
short: 'J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann,
in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.),
Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing,
Cham, 2022, pp. 192–206.'
date_created: 2023-11-14T15:58:58Z
date_updated: 2023-12-13T10:47:50Z
department:
- _id: '819'
doi: 10.1007/978-3-031-14714-2_14
editor:
- first_name: Günter
full_name: Rudolph, Günter
last_name: Rudolph
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Hernán
full_name: Aguirre, Hernán
last_name: Aguirre
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Gabriela
full_name: Ochoa, Gabriela
last_name: Ochoa
- first_name: Tea
full_name: Tusar, Tea
last_name: Tusar
extern: '1'
keyword:
- Anytime behavior
- Benchmarking
- Continuous optimization
- Multi-objective optimization
- Multimodality
- Performance metric
language:
- iso: eng
page: 192–206
place: Cham
publication: Parallel Problem Solving from Nature (PPSN XVII)
publication_identifier:
isbn:
- 978-3-031-14714-2
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: 'BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems'
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '48896'
abstract:
- lang: eng
text: Hardness of Multi-Objective (MO) continuous optimization problems results
from an interplay of various problem characteristics, e. g. the degree of multi-modality.
We present a benchmark study of classical and diversity focused optimizers on
multi-modal MO problems based on automated algorithm configuration. We show the
large effect of the latter and investigate the trade-off between convergence in
objective space and diversity in decision space.
author:
- first_name: Jeroen
full_name: Rook, Jeroen
last_name: Rook
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
citation:
ama: 'Rook J, Trautmann H, Bossek J, Grimme C. On the Potential of Automated Algorithm
Configuration on Multi-Modal Multi-Objective Optimization Problems. In: Proceedings
of the Genetic and Evolutionary Computation Conference Companion. GECCO’22.
Association for Computing Machinery; 2022:356–359. doi:10.1145/3520304.3528998'
apa: Rook, J., Trautmann, H., Bossek, J., & Grimme, C. (2022). On the Potential
of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization
Problems. Proceedings of the Genetic and Evolutionary Computation Conference
Companion, 356–359. https://doi.org/10.1145/3520304.3528998
bibtex: '@inproceedings{Rook_Trautmann_Bossek_Grimme_2022, place={New York, NY,
USA}, series={GECCO’22}, title={On the Potential of Automated Algorithm Configuration
on Multi-Modal Multi-Objective Optimization Problems}, DOI={10.1145/3520304.3528998},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference
Companion}, publisher={Association for Computing Machinery}, author={Rook, Jeroen
and Trautmann, Heike and Bossek, Jakob and Grimme, Christian}, year={2022}, pages={356–359},
collection={GECCO’22} }'
chicago: 'Rook, Jeroen, Heike Trautmann, Jakob Bossek, and Christian Grimme. “On
the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective
Optimization Problems.” In Proceedings of the Genetic and Evolutionary Computation
Conference Companion, 356–359. GECCO’22. New York, NY, USA: Association for
Computing Machinery, 2022. https://doi.org/10.1145/3520304.3528998.'
ieee: 'J. Rook, H. Trautmann, J. Bossek, and C. Grimme, “On the Potential of Automated
Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems,”
in Proceedings of the Genetic and Evolutionary Computation Conference Companion,
2022, pp. 356–359, doi: 10.1145/3520304.3528998.'
mla: Rook, Jeroen, et al. “On the Potential of Automated Algorithm Configuration
on Multi-Modal Multi-Objective Optimization Problems.” Proceedings of the Genetic
and Evolutionary Computation Conference Companion, Association for Computing
Machinery, 2022, pp. 356–359, doi:10.1145/3520304.3528998.
short: 'J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: Proceedings of the Genetic
and Evolutionary Computation Conference Companion, Association for Computing Machinery,
New York, NY, USA, 2022, pp. 356–359.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:50:24Z
department:
- _id: '819'
doi: 10.1145/3520304.3528998
extern: '1'
keyword:
- configuration
- multi-modality
- multi-objective optimization
language:
- iso: eng
page: 356–359
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference Companion
publication_identifier:
isbn:
- 978-1-4503-9268-6
publisher: Association for Computing Machinery
series_title: GECCO’22
status: public
title: On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective
Optimization Problems
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '35206'
author:
- first_name: Bernard
full_name: Bonnard, Bernard
last_name: Bonnard
- first_name: Jérémy
full_name: Rouot, Jérémy
last_name: Rouot
- first_name: Boris Edgar
full_name: Wembe Moafo, Boris Edgar
id: '95394'
last_name: Wembe Moafo
citation:
ama: Bonnard B, Rouot J, Wembe Moafo BE. Accessibility properties of abnormal geodesics
in optimal control illustrated by two case studies. Mathematical Control and
Related Fields. 2022;0(0):0-0. doi:10.3934/mcrf.2022052
apa: Bonnard, B., Rouot, J., & Wembe Moafo, B. E. (2022). Accessibility properties
of abnormal geodesics in optimal control illustrated by two case studies. Mathematical
Control and Related Fields, 0(0), 0–0. https://doi.org/10.3934/mcrf.2022052
bibtex: '@article{Bonnard_Rouot_Wembe Moafo_2022, title={Accessibility properties
of abnormal geodesics in optimal control illustrated by two case studies}, volume={0},
DOI={10.3934/mcrf.2022052},
number={0}, journal={Mathematical Control and Related Fields}, publisher={American
Institute of Mathematical Sciences (AIMS)}, author={Bonnard, Bernard and Rouot,
Jérémy and Wembe Moafo, Boris Edgar}, year={2022}, pages={0–0} }'
chicago: 'Bonnard, Bernard, Jérémy Rouot, and Boris Edgar Wembe Moafo. “Accessibility
Properties of Abnormal Geodesics in Optimal Control Illustrated by Two Case Studies.”
Mathematical Control and Related Fields 0, no. 0 (2022): 0–0. https://doi.org/10.3934/mcrf.2022052.'
ieee: 'B. Bonnard, J. Rouot, and B. E. Wembe Moafo, “Accessibility properties of
abnormal geodesics in optimal control illustrated by two case studies,” Mathematical
Control and Related Fields, vol. 0, no. 0, pp. 0–0, 2022, doi: 10.3934/mcrf.2022052.'
mla: Bonnard, Bernard, et al. “Accessibility Properties of Abnormal Geodesics in
Optimal Control Illustrated by Two Case Studies.” Mathematical Control and
Related Fields, vol. 0, no. 0, American Institute of Mathematical Sciences
(AIMS), 2022, pp. 0–0, doi:10.3934/mcrf.2022052.
short: B. Bonnard, J. Rouot, B.E. Wembe Moafo, Mathematical Control and Related
Fields 0 (2022) 0–0.
date_created: 2023-01-04T10:26:56Z
date_updated: 2023-01-16T12:07:51Z
doi: 10.3934/mcrf.2022052
issue: '0'
keyword:
- Applied Mathematics
- Control and Optimization
- General Medicine
language:
- iso: eng
page: 0-0
publication: Mathematical Control and Related Fields
publication_identifier:
issn:
- 2156-8472
- 2156-8499
publication_status: published
publisher: American Institute of Mathematical Sciences (AIMS)
status: public
title: Accessibility properties of abnormal geodesics in optimal control illustrated
by two case studies
type: journal_article
user_id: '95394'
volume: '0'
year: '2022'
...
---
_id: '47961'
abstract:
- lang: eng
text: Due to failures or even the absence of an electricity grid, microgrid
systems are becoming popular solutions for electrifying African rural communities.
However, they are heavily stressed and complex to control due to their intermittency
and demand growth. Demand side management (DSM) serves as an option to increase
the level of flexibility on the demand side by scheduling users’ consumption patterns
profiles in response to supply. This paper proposes a demand-side management strategy
based on load shifting and peak clipping. The proposed approach was modelled in
a MATLAB/Simulink R2021a environment and was optimized using the artificial neural
network (ANN) algorithm. Simulations were carried out to test the model’s efficacy
in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces
the peak demand, smoothing the load profile to the desired level, and improves
the system’s peak to average ratio (PAR). The presence of deferrable loads has
been considered to bring more flexible demand-side management. Results promise
decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through
peak clipping. In addition, load shifting promises more flexibility to customers.
article_number: '5215'
author:
- first_name: Godiana Hagile
full_name: Philipo, Godiana Hagile
id: '88505'
last_name: Philipo
- first_name: Josephine Nakato
full_name: Kakande, Josephine Nakato
id: '88649'
last_name: Kakande
- first_name: Stefan
full_name: Krauter, Stefan
id: '28836'
last_name: Krauter
orcid: 0000-0002-3594-260X
citation:
ama: Philipo GH, Kakande JN, Krauter S. Neural Network-Based Demand-Side Management
in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.
Energies. 2022;15(14). doi:10.3390/en15145215
apa: Philipo, G. H., Kakande, J. N., & Krauter, S. (2022). Neural Network-Based
Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting
and Peak-Clipping. Energies, 15(14), Article 5215. https://doi.org/10.3390/en15145215
bibtex: '@article{Philipo_Kakande_Krauter_2022, title={Neural Network-Based Demand-Side
Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and
Peak-Clipping}, volume={15}, DOI={10.3390/en15145215},
number={145215}, journal={Energies}, publisher={MDPI AG}, author={Philipo, Godiana
Hagile and Kakande, Josephine Nakato and Krauter, Stefan}, year={2022} }'
chicago: Philipo, Godiana Hagile, Josephine Nakato Kakande, and Stefan Krauter.
“Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery
Microgrid Using Load-Shifting and Peak-Clipping.” Energies 15, no. 14 (2022).
https://doi.org/10.3390/en15145215.
ieee: 'G. H. Philipo, J. N. Kakande, and S. Krauter, “Neural Network-Based Demand-Side
Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and
Peak-Clipping,” Energies, vol. 15, no. 14, Art. no. 5215, 2022, doi: 10.3390/en15145215.'
mla: Philipo, Godiana Hagile, et al. “Neural Network-Based Demand-Side Management
in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.”
Energies, vol. 15, no. 14, 5215, MDPI AG, 2022, doi:10.3390/en15145215.
short: G.H. Philipo, J.N. Kakande, S. Krauter, Energies 15 (2022).
date_created: 2023-10-11T08:13:13Z
date_updated: 2024-10-17T08:46:23Z
department:
- _id: '53'
doi: 10.3390/en15145215
intvolume: ' 15'
issue: '14'
keyword:
- Energy (miscellaneous)
- Energy Engineering and Power Technology
- Renewable Energy
- Sustainability and the Environment
- Electrical and Electronic Engineering
- Control and Optimization
- Engineering (miscellaneous)
- Building and Construction
language:
- iso: eng
publication: Energies
publication_identifier:
issn:
- 1996-1073
publication_status: published
publisher: MDPI AG
status: public
title: Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery
Microgrid Using Load-Shifting and Peak-Clipping
type: journal_article
user_id: '16148'
volume: 15
year: '2022'
...
---
_id: '31066'
abstract:
- lang: eng
text: 'While trade-offs between modeling effort and model accuracy remain a major
concern with system identification, resorting to data-driven methods often leads
to a complete disregard for physical plausibility. To address this issue, we propose
a physics-guided hybrid approach for modeling non-autonomous systems under control.
Starting from a traditional physics-based model, this is extended by a recurrent
neural network and trained using a sophisticated multi-objective strategy yielding
physically plausible models. While purely data-driven methods fail to produce
satisfying results, experiments conducted on real data reveal substantial accuracy
improvements by our approach compared to a physics-based model. '
author:
- first_name: Oliver
full_name: Schön, Oliver
last_name: Schön
- first_name: Ricarda-Samantha
full_name: Götte, Ricarda-Samantha
id: '43992'
last_name: Götte
- first_name: Julia
full_name: Timmermann, Julia
id: '15402'
last_name: Timmermann
citation:
ama: 'Schön O, Götte R-S, Timmermann J. Multi-Objective Physics-Guided Recurrent
Neural Networks for Identifying Non-Autonomous Dynamical Systems. In: 14th
IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022). Vol 55.
; 2022:19-24. doi:https://doi.org/10.1016/j.ifacol.2022.07.282'
apa: Schön, O., Götte, R.-S., & Timmermann, J. (2022). Multi-Objective Physics-Guided
Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. 14th
IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55(12),
19–24. https://doi.org/10.1016/j.ifacol.2022.07.282
bibtex: '@inproceedings{Schön_Götte_Timmermann_2022, title={Multi-Objective Physics-Guided
Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems}, volume={55},
DOI={https://doi.org/10.1016/j.ifacol.2022.07.282},
number={12}, booktitle={14th IFAC Workshop on Adaptive and Learning Control Systems
(ALCOS 2022)}, author={Schön, Oliver and Götte, Ricarda-Samantha and Timmermann,
Julia}, year={2022}, pages={19–24} }'
chicago: Schön, Oliver, Ricarda-Samantha Götte, and Julia Timmermann. “Multi-Objective
Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical
Systems.” In 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS
2022), 55:19–24, 2022. https://doi.org/10.1016/j.ifacol.2022.07.282.
ieee: 'O. Schön, R.-S. Götte, and J. Timmermann, “Multi-Objective Physics-Guided
Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems,” in
14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022),
Casablanca, Morocco, 2022, vol. 55, no. 12, pp. 19–24, doi: https://doi.org/10.1016/j.ifacol.2022.07.282.'
mla: Schön, Oliver, et al. “Multi-Objective Physics-Guided Recurrent Neural Networks
for Identifying Non-Autonomous Dynamical Systems.” 14th IFAC Workshop on Adaptive
and Learning Control Systems (ALCOS 2022), vol. 55, no. 12, 2022, pp. 19–24,
doi:https://doi.org/10.1016/j.ifacol.2022.07.282.
short: 'O. Schön, R.-S. Götte, J. Timmermann, in: 14th IFAC Workshop on Adaptive
and Learning Control Systems (ALCOS 2022), 2022, pp. 19–24.'
conference:
end_date: 2022-07-01
location: Casablanca, Morocco
name: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)
start_date: 2022-06-29
date_created: 2022-05-05T06:22:55Z
date_updated: 2024-11-13T08:43:16Z
department:
- _id: '153'
- _id: '880'
doi: https://doi.org/10.1016/j.ifacol.2022.07.282
intvolume: ' 55'
issue: '12'
keyword:
- neural networks
- physics-guided
- data-driven
- multi-objective optimization
- system identification
- machine learning
- dynamical systems
language:
- iso: eng
page: 19-24
publication: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)
quality_controlled: '1'
status: public
title: Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous
Dynamical Systems
type: conference
user_id: '43992'
volume: 55
year: '2022'
...
---
_id: '29803'
abstract:
- lang: eng
text: "Ultrasonic wire bonding is a solid-state joining process used to form electrical
interconnections in micro and\r\npower electronics and batteries. A high frequency
oscillation causes a metallurgical bond deformation in\r\nthe contact area. Due
to the numerous physical influencing factors, it is very difficult to accurately
capture\r\nthis process in a model. Therefore, our goal is to determine a suitable
feed-forward control strategy for the\r\nbonding process even without detailed
model knowledge. We propose the use of batch constrained Bayesian\r\noptimization
for the control design. Hence, Bayesian optimization is precisely adapted to the
application of\r\nbonding: the constraint is used to check one quality feature
of the process and the use of batches leads to\r\nmore efficient experiments.
Our approach is suitable to determine a feed-forward control for the bonding\r\nprocess
that provides very high quality bonds without using a physical model. We also
show that the quality\r\nof the Bayesian optimization based control outperforms
random search as well as manual search by a user.\r\nUsing a simple prior knowledge
model derived from data further improves the quality of the connection.\r\nThe
Bayesian optimization approach offers the possibility to perform a sensitivity
analysis of the control\r\nparameters, which allows to evaluate the influence
of each control parameter on the bond quality. In summary,\r\nBayesian optimization
applied to the bonding process provides an excellent opportunity to develop a
feedforward\r\ncontrol without full modeling of the underlying physical processes."
author:
- first_name: Michael
full_name: Hesse, Michael
id: '29222'
last_name: Hesse
- first_name: Matthias
full_name: Hunstig, Matthias
last_name: Hunstig
- first_name: Julia
full_name: Timmermann, Julia
id: '15402'
last_name: Timmermann
- first_name: Ansgar
full_name: Trächtler, Ansgar
id: '552'
last_name: Trächtler
citation:
ama: 'Hesse M, Hunstig M, Timmermann J, Trächtler A. Batch Constrained Bayesian
Optimization for UltrasonicWire Bonding Feed-forward Control Design. In: Proceedings
of the 11th International Conference on Pattern Recognition Applications and Methods
(ICPRAM). ; 2022:383-394.'
apa: Hesse, M., Hunstig, M., Timmermann, J., & Trächtler, A. (2022). Batch Constrained
Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design.
Proceedings of the 11th International Conference on Pattern Recognition Applications
and Methods (ICPRAM), 383–394.
bibtex: '@inproceedings{Hesse_Hunstig_Timmermann_Trächtler_2022, title={Batch Constrained
Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design},
booktitle={Proceedings of the 11th International Conference on Pattern Recognition
Applications and Methods (ICPRAM)}, author={Hesse, Michael and Hunstig, Matthias
and Timmermann, Julia and Trächtler, Ansgar}, year={2022}, pages={383–394} }'
chicago: Hesse, Michael, Matthias Hunstig, Julia Timmermann, and Ansgar Trächtler.
“Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-Forward
Control Design.” In Proceedings of the 11th International Conference on Pattern
Recognition Applications and Methods (ICPRAM), 383–94, 2022.
ieee: M. Hesse, M. Hunstig, J. Timmermann, and A. Trächtler, “Batch Constrained
Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design,”
in Proceedings of the 11th International Conference on Pattern Recognition
Applications and Methods (ICPRAM), Online, 2022, pp. 383–394.
mla: Hesse, Michael, et al. “Batch Constrained Bayesian Optimization for UltrasonicWire
Bonding Feed-Forward Control Design.” Proceedings of the 11th International
Conference on Pattern Recognition Applications and Methods (ICPRAM), 2022,
pp. 383–94.
short: 'M. Hesse, M. Hunstig, J. Timmermann, A. Trächtler, in: Proceedings of the
11th International Conference on Pattern Recognition Applications and Methods
(ICPRAM), 2022, pp. 383–394.'
conference:
end_date: 2022-02-05
location: Online
name: 11th International Conference on Pattern Recognition Applications and Methods
start_date: 2022-02-03
date_created: 2022-02-09T12:50:25Z
date_updated: 2024-11-13T08:44:17Z
department:
- _id: '153'
- _id: '880'
keyword:
- Bayesian optimization
- Wire bonding
- Feed-forward control
- model-free design
language:
- iso: eng
page: 383-394
publication: Proceedings of the 11th International Conference on Pattern Recognition
Applications and Methods (ICPRAM)
publication_identifier:
isbn:
- 978-989-758-549-4
quality_controlled: '1'
status: public
title: Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward
Control Design
type: conference
user_id: '82875'
year: '2022'
...