---
_id: '63838'
abstract:
- lang: eng
text: "Industrial electrification is increasing to reduce fossil fuel dependence,
alongside a growing share of volatile renewables.\r\nA secure and reliable energy
supply is crucial for industry, leading to a shift from centralised to decentralised
grid structures.\r\nDC microgrids becoming increasingly popular in industry, since
they enable energy recuperation from braking, reduce components and cables, and
integrate storage and local generation to manage supply interruptions or peak
loads.\r\nEVs add further synergies by serving as mobile storage units, helping
to store and redistribute locally generated renewable energy.\r\nThis paper analyses
how EV integration in droop-controlled DC grids can contribute to a more stable,
low-emission and peak-reduced load profile to the supply grid through load shifting
and bridge interruptions.\r\nA droop-controlled DC grid model has been developed,
incorporating an EV charging park based on probability functions.\r\nScalable
scenarios allow for diverse condition analysis using an energy management system
that utilises fuzzy logic and sequential MILP optimisation.\r\nIt has been shown
that a 7% improvement of coefficient represented grid-serving behaviour is possible
by load shifting.\r\nIt has also been demonstrated that an optimised EMS can reduce
the demand-based CO2 emissions by 41kg for a representative day compared to a
fuzzy logic EMS.\r\nAt the same time peak load is decreased yielding a more constant
residual load.\r\nThese results highlight the potential of a controlled bidirectional
charging infrastructure in DC grids and underscore the need to explicitly consider
charging processes to ensure a residual load as constant as possible."
article_number: '100227'
article_type: original
author:
- first_name: Henning Christoph
full_name: Rahlf, Henning Christoph
id: '56955'
last_name: Rahlf
orcid: 0009-0006-8106-2132
- first_name: Lukas
full_name: Knorr, Lukas
id: '90391'
last_name: Knorr
orcid: 0009-0005-4727-7511
- first_name: Simon
full_name: Althoff, Simon
last_name: Althoff
- first_name: Henning
full_name: Meschede, Henning
id: '86954'
last_name: Meschede
orcid: 0000-0002-1538-089X
citation:
ama: Rahlf HC, Knorr L, Althoff S, Meschede H. Analysis of bidirectional EV charging
infrastructures within industrial DC grids. Smart Energy. Published online
2026. doi:10.1016/j.segy.2026.100227
apa: Rahlf, H. C., Knorr, L., Althoff, S., & Meschede, H. (2026). Analysis of
bidirectional EV charging infrastructures within industrial DC grids. Smart
Energy, Article 100227. https://doi.org/10.1016/j.segy.2026.100227
bibtex: '@article{Rahlf_Knorr_Althoff_Meschede_2026, title={Analysis of bidirectional
EV charging infrastructures within industrial DC grids}, DOI={10.1016/j.segy.2026.100227},
number={100227}, journal={Smart Energy}, publisher={Elsevier BV}, author={Rahlf,
Henning Christoph and Knorr, Lukas and Althoff, Simon and Meschede, Henning},
year={2026} }'
chicago: Rahlf, Henning Christoph, Lukas Knorr, Simon Althoff, and Henning Meschede.
“Analysis of Bidirectional EV Charging Infrastructures within Industrial DC Grids.”
Smart Energy, 2026. https://doi.org/10.1016/j.segy.2026.100227.
ieee: 'H. C. Rahlf, L. Knorr, S. Althoff, and H. Meschede, “Analysis of bidirectional
EV charging infrastructures within industrial DC grids,” Smart Energy,
Art. no. 100227, 2026, doi: 10.1016/j.segy.2026.100227.'
mla: Rahlf, Henning Christoph, et al. “Analysis of Bidirectional EV Charging Infrastructures
within Industrial DC Grids.” Smart Energy, 100227, Elsevier BV, 2026, doi:10.1016/j.segy.2026.100227.
short: H.C. Rahlf, L. Knorr, S. Althoff, H. Meschede, Smart Energy (2026).
date_created: 2026-02-02T14:45:17Z
date_updated: 2026-02-03T12:58:44Z
department:
- _id: '644'
doi: 10.1016/j.segy.2026.100227
keyword:
- DC-grid
- Droop control
- Grid-serving behaviour
- Grid stability
- Bidirectional charging
- Sequential decision
- MILP optimisation
language:
- iso: eng
publication: Smart Energy
publication_identifier:
issn:
- 2666-9552
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: Analysis of bidirectional EV charging infrastructures within industrial DC
grids
type: journal_article
user_id: '56955'
year: '2026'
...
---
_id: '48894'
abstract:
- lang: eng
text: Recently different evolutionary computation approaches have been developed
that generate sets of high quality diverse solutions for a given optimisation
problem. Many studies have considered diversity 1) as a mean to explore niches
in behavioural space (quality diversity) or 2) to increase the structural differences
of solutions (evolutionary diversity optimisation). In this study, we introduce
a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component
traveling thief problem. The results show the capability of the co-evolutionary
algorithm to achieve significantly higher diversity compared to the baseline evolutionary
diversity algorithms from the literature.
author:
- first_name: Adel
full_name: Nikfarjam, Adel
last_name: Nikfarjam
- first_name: Aneta
full_name: Neumann, Aneta
last_name: Neumann
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Nikfarjam A, Neumann A, Bossek J, Neumann F. Co-Evolutionary Diversity Optimisation
for the Traveling Thief Problem. In: Rudolph G, Kononova AV, Aguirre H, Kerschke
P, Ochoa G, Tu\v sar T, eds. Parallel Problem Solving from Nature (PPSN XVII).
Lecture Notes in Computer Science. Springer International Publishing; 2022:237–249.
doi:10.1007/978-3-031-14714-2_17'
apa: Nikfarjam, A., Neumann, A., Bossek, J., & Neumann, F. (2022). Co-Evolutionary
Diversity Optimisation for the Traveling Thief Problem. In G. Rudolph, A. V. Kononova,
H. Aguirre, P. Kerschke, G. Ochoa, & T. Tu\v sar (Eds.), Parallel Problem
Solving from Nature (PPSN XVII) (pp. 237–249). Springer International Publishing.
https://doi.org/10.1007/978-3-031-14714-2_17
bibtex: '@inproceedings{Nikfarjam_Neumann_Bossek_Neumann_2022, place={Cham}, series={Lecture
Notes in Computer Science}, title={Co-Evolutionary Diversity Optimisation for
the Traveling Thief Problem}, DOI={10.1007/978-3-031-14714-2_17},
booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer
International Publishing}, author={Nikfarjam, Adel and Neumann, Aneta and Bossek,
Jakob and Neumann, Frank}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre,
Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tu\v sar, Tea}, year={2022},
pages={237–249}, collection={Lecture Notes in Computer Science} }'
chicago: 'Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary
Diversity Optimisation for the Traveling Thief Problem.” In Parallel Problem
Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova,
Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\v sar, 237–249. Lecture
Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_17.'
ieee: 'A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity
Optimisation for the Traveling Thief Problem,” in Parallel Problem Solving
from Nature (PPSN XVII), 2022, pp. 237–249, doi: 10.1007/978-3-031-14714-2_17.'
mla: Nikfarjam, Adel, et al. “Co-Evolutionary Diversity Optimisation for the Traveling
Thief Problem.” Parallel Problem Solving from Nature (PPSN XVII), edited
by Günter Rudolph et al., Springer International Publishing, 2022, pp. 237–249,
doi:10.1007/978-3-031-14714-2_17.
short: 'A. Nikfarjam, A. Neumann, J. Bossek, F. Neumann, in: G. Rudolph, A.V. Kononova,
H. Aguirre, P. Kerschke, G. Ochoa, T. Tu\v sar (Eds.), Parallel Problem Solving
from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 237–249.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:49:51Z
department:
- _id: '819'
doi: 10.1007/978-3-031-14714-2_17
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: Tu\v sar, Tea
last_name: Tu\v sar
extern: '1'
keyword:
- Co-evolutionary algorithms
- Evolutionary diversity optimisation
- Quality diversity
- Traveling thief problem
language:
- iso: eng
page: 237–249
place: Cham
publication: Parallel Problem Solving from Nature (PPSN XVII)
publication_identifier:
isbn:
- 978-3-031-14714-2
publication_status: published
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '48893'
abstract:
- lang: eng
text: Computing diverse sets of high-quality solutions has gained increasing attention
among the evolutionary computation community in recent years. It allows practitioners
to choose from a set of high-quality alternatives. In this paper, we employ a
population diversity measure, called the high-order entropy measure, in an evolutionary
algorithm to compute a diverse set of high-quality solutions for the Traveling
Salesperson Problem. In contrast to previous studies, our approach allows diversifying
segments of tours containing several edges based on the entropy measure. We examine
the resulting evolutionary diversity optimisation approach precisely in terms
of the final set of solutions and theoretical properties. Experimental results
show significant improvements compared to a recently proposed edge-based diversity
optimisation approach when working with a large population of solutions or long
segments.
author:
- first_name: Adel
full_name: Nikfarjam, Adel
last_name: Nikfarjam
- 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: 'Nikfarjam A, Bossek J, Neumann A, Neumann F. Entropy-Based Evolutionary Diversity
Optimisation for the Traveling Salesperson Problem. In: Proceedings of the
Genetic and Evolutionary Computation Conference. GECCO’21. Association for
Computing Machinery; 2021:600–608. doi:10.1145/3449639.3459384'
apa: Nikfarjam, A., Bossek, J., Neumann, A., & Neumann, F. (2021). Entropy-Based
Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. Proceedings
of the Genetic and Evolutionary Computation Conference, 600–608. https://doi.org/10.1145/3449639.3459384
bibtex: '@inproceedings{Nikfarjam_Bossek_Neumann_Neumann_2021, place={New York,
NY, USA}, series={GECCO’21}, title={Entropy-Based Evolutionary Diversity Optimisation
for the Traveling Salesperson Problem}, DOI={10.1145/3449639.3459384},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Nikfarjam, Adel and Bossek,
Jakob and Neumann, Aneta and Neumann, Frank}, year={2021}, pages={600–608}, collection={GECCO’21}
}'
chicago: 'Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Entropy-Based
Evolutionary Diversity Optimisation for the Traveling Salesperson Problem.” In
Proceedings of the Genetic and Evolutionary Computation Conference, 600–608.
GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3449639.3459384.'
ieee: 'A. Nikfarjam, J. Bossek, A. Neumann, and F. Neumann, “Entropy-Based Evolutionary
Diversity Optimisation for the Traveling Salesperson Problem,” in Proceedings
of the Genetic and Evolutionary Computation Conference, 2021, pp. 600–608,
doi: 10.1145/3449639.3459384.'
mla: Nikfarjam, Adel, et al. “Entropy-Based Evolutionary Diversity Optimisation
for the Traveling Salesperson Problem.” Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, 2021, pp. 600–608,
doi:10.1145/3449639.3459384.
short: 'A. Nikfarjam, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the
Genetic and Evolutionary Computation Conference, Association for Computing Machinery,
New York, NY, USA, 2021, pp. 600–608.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:50:06Z
department:
- _id: '819'
doi: 10.1145/3449639.3459384
extern: '1'
keyword:
- evolutionary algorithms
- evolutionary diversity optimisation
- high-order entropy
- traveling salesperson problem
language:
- iso: eng
page: 600–608
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-8350-9
publisher: Association for Computing Machinery
series_title: GECCO’21
status: public
title: Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson
Problem
type: conference
user_id: '102979'
year: '2021'
...
---
_id: '48891'
abstract:
- lang: eng
text: Submodular functions allow to model many real-world optimisation problems.
This paper introduces approaches for computing diverse sets of high quality solutions
for submodular optimisation problems with uniform and knapsack constraints. We
first present diversifying greedy sampling approaches and analyse them with respect
to the diversity measured by entropy and the approximation quality of the obtained
solutions. Afterwards, we introduce an evolutionary diversity optimisation (EDO)
approach to further improve diversity of the set of solutions. We carry out experimental
investigations on popular submodular benchmark problems and analyse trade-offs
in terms of solution quality and diversity of the resulting solution sets.
author:
- first_name: Aneta
full_name: Neumann, Aneta
last_name: Neumann
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Neumann A, Bossek J, Neumann F. Diversifying Greedy Sampling and Evolutionary
Diversity Optimisation for Constrained Monotone Submodular Functions. In: Proceedings
of the Genetic and Evolutionary Computation Conference. GECCO’21. Association
for Computing Machinery; 2021:261–269. doi:10.1145/3449639.3459385'
apa: Neumann, A., Bossek, J., & Neumann, F. (2021). Diversifying Greedy Sampling
and Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions.
Proceedings of the Genetic and Evolutionary Computation Conference, 261–269.
https://doi.org/10.1145/3449639.3459385
bibtex: '@inproceedings{Neumann_Bossek_Neumann_2021, place={New York, NY, USA},
series={GECCO’21}, title={Diversifying Greedy Sampling and Evolutionary Diversity
Optimisation for Constrained Monotone Submodular Functions}, DOI={10.1145/3449639.3459385},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Neumann, Aneta and Bossek,
Jakob and Neumann, Frank}, year={2021}, pages={261–269}, collection={GECCO’21}
}'
chicago: 'Neumann, Aneta, Jakob Bossek, and Frank Neumann. “Diversifying Greedy
Sampling and Evolutionary Diversity Optimisation for Constrained Monotone Submodular
Functions.” In Proceedings of the Genetic and Evolutionary Computation Conference,
261–269. GECCO’21. New York, NY, USA: Association for Computing Machinery, 2021.
https://doi.org/10.1145/3449639.3459385.'
ieee: 'A. Neumann, J. Bossek, and F. Neumann, “Diversifying Greedy Sampling and
Evolutionary Diversity Optimisation for Constrained Monotone Submodular Functions,”
in Proceedings of the Genetic and Evolutionary Computation Conference,
2021, pp. 261–269, doi: 10.1145/3449639.3459385.'
mla: Neumann, Aneta, et al. “Diversifying Greedy Sampling and Evolutionary Diversity
Optimisation for Constrained Monotone Submodular Functions.” Proceedings of
the Genetic and Evolutionary Computation Conference, Association for Computing
Machinery, 2021, pp. 261–269, doi:10.1145/3449639.3459385.
short: 'A. Neumann, J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, New York, NY, USA,
2021, pp. 261–269.'
date_created: 2023-11-14T15:58:59Z
date_updated: 2023-12-13T10:49:25Z
department:
- _id: '819'
doi: 10.1145/3449639.3459385
extern: '1'
keyword:
- evolutionary algorithms
- evolutionary diversity optimisation
- sub-modular functions
language:
- iso: eng
page: 261–269
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-8350-9
publisher: Association for Computing Machinery
series_title: GECCO’21
status: public
title: Diversifying Greedy Sampling and Evolutionary Diversity Optimisation for Constrained
Monotone Submodular Functions
type: conference
user_id: '102979'
year: '2021'
...
---
_id: '48892'
abstract:
- lang: eng
text: Evolutionary algorithms based on edge assembly crossover (EAX) constitute
some of the best performing incomplete solvers for the well-known traveling salesperson
problem (TSP). Often, it is desirable to compute not just a single solution for
a given problem, but a diverse set of high quality solutions from which a decision
maker can choose one for implementation. Currently, there are only a few approaches
for computing a diverse solution set for the TSP. Furthermore, almost all of them
assume that the optimal solution is known. In this paper, we introduce evolutionary
diversity optimisation (EDO) approaches for the TSP that find a diverse set of
tours when the optimal tour is known or unknown. We show how to adopt EAX to not
only find a high-quality solution but also to maximise the diversity of the population.
The resulting EAX-based EDO approach, termed EAX-EDO is capable of obtaining diverse
high-quality tours when the optimal solution for the TSP is known or unknown.
A comparison to existing approaches shows that they are clearly outperformed by
EAX-EDO.
author:
- first_name: Adel
full_name: Nikfarjam, Adel
last_name: Nikfarjam
- 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: 'Nikfarjam A, Bossek J, Neumann A, Neumann F. Computing Diverse Sets of High
Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation. In: Proceedings
of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms. Association
for Computing Machinery; 2021:1–11.'
apa: Nikfarjam, A., Bossek, J., Neumann, A., & Neumann, F. (2021). Computing
Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation.
In Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic
Algorithms (pp. 1–11). Association for Computing Machinery.
bibtex: '@inbook{Nikfarjam_Bossek_Neumann_Neumann_2021, place={New York, NY, USA},
title={Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary
Diversity Optimisation}, booktitle={Proceedings of the 16th ACM}/SIGEVO Conference
on Foundations of Genetic Algorithms}, publisher={Association for Computing Machinery},
author={Nikfarjam, Adel and Bossek, Jakob and Neumann, Aneta and Neumann, Frank},
year={2021}, pages={1–11} }'
chicago: 'Nikfarjam, Adel, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Computing
Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation.”
In Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic
Algorithms, 1–11. New York, NY, USA: Association for Computing Machinery,
2021.'
ieee: 'A. Nikfarjam, J. Bossek, A. Neumann, and F. Neumann, “Computing Diverse Sets
of High Quality TSP Tours by EAX-based Evolutionary Diversity Optimisation,” in
Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms,
New York, NY, USA: Association for Computing Machinery, 2021, pp. 1–11.'
mla: Nikfarjam, Adel, et al. “Computing Diverse Sets of High Quality TSP Tours by
EAX-Based Evolutionary Diversity Optimisation.” Proceedings of the 16th ACM}/SIGEVO
Conference on Foundations of Genetic Algorithms, Association for Computing
Machinery, 2021, pp. 1–11.
short: 'A. Nikfarjam, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the
16th ACM}/SIGEVO Conference on Foundations of Genetic Algorithms, Association
for Computing Machinery, New York, NY, USA, 2021, pp. 1–11.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:49:59Z
department:
- _id: '819'
extern: '1'
keyword:
- edge assembly crossover (EAX)
- evolutionary algorithms
- evolutionary diversity optimisation (EDO)
- traveling salesperson problem (TSP)
language:
- iso: eng
page: 1–11
place: New York, NY, USA
publication: Proceedings of the 16th ACM}/SIGEVO Conference on Foundations of Genetic
Algorithms
publication_identifier:
isbn:
- 978-1-4503-8352-3
publisher: Association for Computing Machinery
status: public
title: Computing Diverse Sets of High Quality TSP Tours by EAX-based Evolutionary
Diversity Optimisation
type: book_chapter
user_id: '102979'
year: '2021'
...
---
_id: '9760'
abstract:
- lang: eng
text: Self-optimizing systems are able to adapt their behavior autonomously according
to their current self-determined objectives. Unforeseen influences could lead
to dependability-critical behavior of the system. Methods are required which secure
self-optimizing systems during operation. These methods to increase the dependability
of the system should already be taken into consideration in the design process.
This paper presents a guideline for the dependability-oriented design of self-optimizing
systems, which integrates established classical methods like failure mode and
effects analysis as well as methods based on self-optimization. On the one hand
self-optimization is used to increase the dependability of the system by integrating
objectives like safety, availability, and reliability to the objectives of the
system. On the other hand methods are required to ensure the self-optimization
itself. As basis for this guideline serves the principle solution of the system.
The six phases of the guideline extend the design process and lead to an enhanced
principle solution. Additionally, the guideline illustrates phases to implement
and validate the self-optimizing system. The proposed guideline is applied to
an innovative rail-bound vehicle, called RailCab, which is equipped with self-optimizing
function modules.
author:
- first_name: Christoph
full_name: Sondermann-Wölke, Christoph
last_name: Sondermann-Wölke
- first_name: Tobias
full_name: Hemsel, Tobias
id: '210'
last_name: Hemsel
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
- first_name: Jürgen
full_name: Gausemeier, Jürgen
last_name: Gausemeier
- first_name: Sebastian
full_name: Pook, Sebastian
last_name: Pook
citation:
ama: 'Sondermann-Wölke C, Hemsel T, Sextro W, Gausemeier J, Pook S. Guideline for
the dependability-oriented design of self-optimizing systems. In: Industrial
Informatics (INDIN), 2010 8th IEEE International Conference On. ; 2010:739-744.
doi:10.1109/INDIN.2010.5549490'
apa: Sondermann-Wölke, C., Hemsel, T., Sextro, W., Gausemeier, J., & Pook, S.
(2010). Guideline for the dependability-oriented design of self-optimizing systems.
In Industrial Informatics (INDIN), 2010 8th IEEE International Conference on
(pp. 739–744). https://doi.org/10.1109/INDIN.2010.5549490
bibtex: '@inproceedings{Sondermann-Wölke_Hemsel_Sextro_Gausemeier_Pook_2010, title={Guideline
for the dependability-oriented design of self-optimizing systems}, DOI={10.1109/INDIN.2010.5549490},
booktitle={Industrial Informatics (INDIN), 2010 8th IEEE International Conference
on}, author={Sondermann-Wölke, Christoph and Hemsel, Tobias and Sextro, Walter
and Gausemeier, Jürgen and Pook, Sebastian}, year={2010}, pages={739–744} }'
chicago: Sondermann-Wölke, Christoph, Tobias Hemsel, Walter Sextro, Jürgen Gausemeier,
and Sebastian Pook. “Guideline for the Dependability-Oriented Design of Self-Optimizing
Systems.” In Industrial Informatics (INDIN), 2010 8th IEEE International Conference
On, 739–44, 2010. https://doi.org/10.1109/INDIN.2010.5549490.
ieee: C. Sondermann-Wölke, T. Hemsel, W. Sextro, J. Gausemeier, and S. Pook, “Guideline
for the dependability-oriented design of self-optimizing systems,” in Industrial
Informatics (INDIN), 2010 8th IEEE International Conference on, 2010, pp.
739–744.
mla: Sondermann-Wölke, Christoph, et al. “Guideline for the Dependability-Oriented
Design of Self-Optimizing Systems.” Industrial Informatics (INDIN), 2010 8th
IEEE International Conference On, 2010, pp. 739–44, doi:10.1109/INDIN.2010.5549490.
short: 'C. Sondermann-Wölke, T. Hemsel, W. Sextro, J. Gausemeier, S. Pook, in: Industrial
Informatics (INDIN), 2010 8th IEEE International Conference On, 2010, pp. 739–744.'
date_created: 2019-05-13T10:25:26Z
date_updated: 2022-01-06T07:04:19Z
department:
- _id: '151'
doi: 10.1109/INDIN.2010.5549490
keyword:
- RailCab
- dependability-critical behavior
- dependability-oriented design
- failure mode
- rail-bound vehicle
- secure self-optimizing systems
- self-optimizing function modules
- optimisation
- railways
- self-adjusting systems
language:
- iso: eng
page: 739 -744
publication: Industrial Informatics (INDIN), 2010 8th IEEE International Conference
on
quality_controlled: '1'
status: public
title: Guideline for the dependability-oriented design of self-optimizing systems
type: conference
user_id: '55222'
year: '2010'
...
---
_id: '46411'
abstract:
- lang: eng
text: The paper presents a framework to optimise the design of work roll based on
the cooling performance. The framework develops meta-models from a set of finite
element analyses (FEA) of the roll cooling. A design of experiment technique is
used to identify the FEA runs. The research also identifies sources of uncertainties
in the design process. A robust evolutionary multi-objective evaluation technique
is applied to the design optimisation in constrained problems with real life uncertainty.
The approach handles uncertainties associated both with design variables and fitness
functions. Constraints violation within the neighbourhood of a design is considered
as part of a measurement for degree of feasibility and robustness of a solution.
author:
- first_name: Y.T.
full_name: Azene, Y.T.
last_name: Azene
- first_name: R.
full_name: Roy, R.
last_name: Roy
- first_name: D.
full_name: Farrugia, D.
last_name: Farrugia
- first_name: C.
full_name: Onisa, C.
last_name: Onisa
- first_name: J.
full_name: Mehnen, J.
last_name: Mehnen
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: Azene YT, Roy R, Farrugia D, Onisa C, Mehnen J, Trautmann H. Work roll cooling
system design optimisation in presence of uncertainty and constrains. CIRP
Journal of Manufacturing Science and Technology. 2010;2(4):290-298. doi:https://doi.org/10.1016/j.cirpj.2010.06.001
apa: Azene, Y. T., Roy, R., Farrugia, D., Onisa, C., Mehnen, J., & Trautmann,
H. (2010). Work roll cooling system design optimisation in presence of uncertainty
and constrains. CIRP Journal of Manufacturing Science and Technology, 2(4),
290–298. https://doi.org/10.1016/j.cirpj.2010.06.001
bibtex: '@article{Azene_Roy_Farrugia_Onisa_Mehnen_Trautmann_2010, title={Work roll
cooling system design optimisation in presence of uncertainty and constrains},
volume={2}, DOI={https://doi.org/10.1016/j.cirpj.2010.06.001},
number={4}, journal={CIRP Journal of Manufacturing Science and Technology}, author={Azene,
Y.T. and Roy, R. and Farrugia, D. and Onisa, C. and Mehnen, J. and Trautmann,
Heike}, year={2010}, pages={290–298} }'
chicago: 'Azene, Y.T., R. Roy, D. Farrugia, C. Onisa, J. Mehnen, and Heike Trautmann.
“Work Roll Cooling System Design Optimisation in Presence of Uncertainty and Constrains.”
CIRP Journal of Manufacturing Science and Technology 2, no. 4 (2010): 290–98.
https://doi.org/10.1016/j.cirpj.2010.06.001.'
ieee: 'Y. T. Azene, R. Roy, D. Farrugia, C. Onisa, J. Mehnen, and H. Trautmann,
“Work roll cooling system design optimisation in presence of uncertainty and constrains,”
CIRP Journal of Manufacturing Science and Technology, vol. 2, no. 4, pp.
290–298, 2010, doi: https://doi.org/10.1016/j.cirpj.2010.06.001.'
mla: Azene, Y. T., et al. “Work Roll Cooling System Design Optimisation in Presence
of Uncertainty and Constrains.” CIRP Journal of Manufacturing Science and Technology,
vol. 2, no. 4, 2010, pp. 290–98, doi:https://doi.org/10.1016/j.cirpj.2010.06.001.
short: Y.T. Azene, R. Roy, D. Farrugia, C. Onisa, J. Mehnen, H. Trautmann, CIRP
Journal of Manufacturing Science and Technology 2 (2010) 290–298.
date_created: 2023-08-04T16:09:19Z
date_updated: 2023-10-16T13:57:23Z
department:
- _id: '34'
- _id: '819'
doi: https://doi.org/10.1016/j.cirpj.2010.06.001
intvolume: ' 2'
issue: '4'
keyword:
- Roll cooling design
- Uncertainty
- Design optimisation
- Multi-objective optimisation
- Constraint in design
language:
- iso: eng
page: 290-298
publication: CIRP Journal of Manufacturing Science and Technology
publication_identifier:
issn:
- 1755-5817
status: public
title: Work roll cooling system design optimisation in presence of uncertainty and
constrains
type: journal_article
user_id: '15504'
volume: 2
year: '2010'
...
---
_id: '11930'
abstract:
- lang: eng
text: For human-machine interfaces in distant-talking environments multichannel
signal processing is often employed to obtain an enhanced signal for subsequent
processing. In this paper we propose a novel adaptation algorithm for a filter-and-sum
beamformer to adjust the coefficients of FIR filters to changing acoustic room
impulses, e.g. due to speaker movement. A deterministic and a stochastic gradient
ascent algorithm are derived from a constrained optimization problem, which iteratively
estimates the eigenvector corresponding to the largest eigenvalue of the cross
power spectral density of the microphone signals. The method does not require
an explicit estimation of the speaker location. The experimental results show
fast adaptation and excellent robustness of the proposed algorithm.
author:
- first_name: Ernst
full_name: Warsitz, Ernst
last_name: Warsitz
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: 'Warsitz E, Haeb-Umbach R. Acoustic filter-and-sum beamforming by adaptive
principal component analysis. In: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2005). Vol 4. ; 2005:iv/797-iv/800 Vol.
4. doi:10.1109/ICASSP.2005.1416129'
apa: Warsitz, E., & Haeb-Umbach, R. (2005). Acoustic filter-and-sum beamforming
by adaptive principal component analysis. In IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2005) (Vol. 4, p. iv/797-iv/800
Vol. 4). https://doi.org/10.1109/ICASSP.2005.1416129
bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2005, title={Acoustic filter-and-sum
beamforming by adaptive principal component analysis}, volume={4}, DOI={10.1109/ICASSP.2005.1416129},
booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2005)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2005},
pages={iv/797-iv/800 Vol. 4} }'
chicago: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming
by Adaptive Principal Component Analysis.” In IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP 2005), 4:iv/797-iv/800
Vol. 4, 2005. https://doi.org/10.1109/ICASSP.2005.1416129.
ieee: E. Warsitz and R. Haeb-Umbach, “Acoustic filter-and-sum beamforming by adaptive
principal component analysis,” in IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2005), 2005, vol. 4, p. iv/797-iv/800
Vol. 4.
mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming
by Adaptive Principal Component Analysis.” IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP 2005), vol. 4, 2005, p. iv/797-iv/800
Vol. 4, doi:10.1109/ICASSP.2005.1416129.
short: 'E. Warsitz, R. Haeb-Umbach, in: IEEE International Conference on Acoustics,
Speech and Signal Processing (ICASSP 2005), 2005, p. iv/797-iv/800 Vol. 4.'
date_created: 2019-07-12T05:31:00Z
date_updated: 2022-01-06T06:51:12Z
department:
- _id: '54'
doi: 10.1109/ICASSP.2005.1416129
intvolume: ' 4'
keyword:
- acoustic filter-and-sum beamforming
- acoustic room impulses
- acoustic signal processing
- adaptive principal component analysis
- adaptive signal processing
- architectural acoustics
- constrained optimization problem
- cross power spectral density
- deterministic algorithm
- deterministic algorithms
- distant-talking environments
- eigenvalues and eigenfunctions
- eigenvector
- enhanced signal
- filter-and-sum beamformer
- FIR filter coefficients
- FIR filter coefficients
- FIR filters
- gradient methods
- human-machine interfaces
- iterative estimation
- iterative methods
- largest eigenvalue
- microphone signals
- multichannel signal processing
- optimisation
- principal component analysis
- spectral analysis
- stochastic gradient ascent algorithm
- stochastic processes
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2005/WaHa05.pdf
oa: '1'
page: iv/797-iv/800 Vol. 4
publication: IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP 2005)
status: public
title: Acoustic filter-and-sum beamforming by adaptive principal component analysis
type: conference
user_id: '44006'
volume: 4
year: '2005'
...