---
_id: '19973'
abstract:
- lang: eng
text: As a result of lightweight design, increased use is being made of high-strength
steel and aluminium in car bodies. Self-piercing riveting is an established technique
for joining these materials. The dissimilar properties of the two materials have
led to a number of different rivet geometries in the past. Each rivet geometry
fulfils the requirements of the materials within a limited range. In the present
investigation, an improved rivet geometry is developed, which permits the reliable
joining of two material combinations that could only be joined by two different
rivet geometries up until now. Material combination 1 consists of high-strength
steel on both sides, while material combination 2 comprises aluminium on the punch
side and high-strength steel on the die side. The material flow and the stress
and strain conditions prevailing during the joining process are analysed by means
of numerical simulation. The rivet geometry is then improved step-by-step on the
basis of this analysis. Finally, the improved rivet geometry is manufactured and
the findings of the investigation are verified in experimental joining tests.
article_type: original
author:
- first_name: Benedikt
full_name: Uhe, Benedikt
id: '38131'
last_name: Uhe
- first_name: Clara-Maria
full_name: Kuball, Clara-Maria
last_name: Kuball
- first_name: Marion
full_name: Merklein, Marion
last_name: Merklein
- first_name: Gerson
full_name: Meschut, Gerson
id: '32056'
last_name: Meschut
orcid: 0000-0002-2763-1246
citation:
ama: Uhe B, Kuball C-M, Merklein M, Meschut G. Improvement of a rivet geometry for
the self-piercing riveting of high-strength steel and multi-material joints. Production
Engineering. 2020;14:417-423. doi:10.1007/s11740-020-00973-w
apa: Uhe, B., Kuball, C.-M., Merklein, M., & Meschut, G. (2020). Improvement
of a rivet geometry for the self-piercing riveting of high-strength steel and
multi-material joints. Production Engineering, 14, 417–423. https://doi.org/10.1007/s11740-020-00973-w
bibtex: '@article{Uhe_Kuball_Merklein_Meschut_2020, title={Improvement of a rivet
geometry for the self-piercing riveting of high-strength steel and multi-material
joints}, volume={14}, DOI={10.1007/s11740-020-00973-w},
journal={Production Engineering}, author={Uhe, Benedikt and Kuball, Clara-Maria
and Merklein, Marion and Meschut, Gerson}, year={2020}, pages={417–423} }'
chicago: 'Uhe, Benedikt, Clara-Maria Kuball, Marion Merklein, and Gerson Meschut.
“Improvement of a Rivet Geometry for the Self-Piercing Riveting of High-Strength
Steel and Multi-Material Joints.” Production Engineering 14 (2020): 417–23.
https://doi.org/10.1007/s11740-020-00973-w.'
ieee: 'B. Uhe, C.-M. Kuball, M. Merklein, and G. Meschut, “Improvement of a rivet
geometry for the self-piercing riveting of high-strength steel and multi-material
joints,” Production Engineering, vol. 14, pp. 417–423, 2020, doi: 10.1007/s11740-020-00973-w.'
mla: Uhe, Benedikt, et al. “Improvement of a Rivet Geometry for the Self-Piercing
Riveting of High-Strength Steel and Multi-Material Joints.” Production Engineering,
vol. 14, 2020, pp. 417–23, doi:10.1007/s11740-020-00973-w.
short: B. Uhe, C.-M. Kuball, M. Merklein, G. Meschut, Production Engineering 14
(2020) 417–423.
date_created: 2020-10-12T08:14:13Z
date_updated: 2023-04-28T09:20:41Z
department:
- _id: '157'
doi: 10.1007/s11740-020-00973-w
intvolume: ' 14'
keyword:
- Self-piercing riveting
- Joining technology
- Rivet geometry
- Multi-material design
- High-strength steel
- Aluminium
language:
- iso: eng
page: 417-423
publication: Production Engineering
publication_status: published
quality_controlled: '1'
status: public
title: Improvement of a rivet geometry for the self-piercing riveting of high-strength
steel and multi-material joints
type: journal_article
user_id: '38131'
volume: 14
year: '2020'
...
---
_id: '46334'
abstract:
- lang: eng
text: We build upon a recently proposed multi-objective view onto performance measurement
of single-objective stochastic solvers. The trade-off between the fraction of
failed runs and the mean runtime of successful runs – both to be minimized – is
directly analyzed based on a study on algorithm selection of inexact state-of-the-art
solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt
the hypervolume indicator (HV) commonly used in multi-objective optimization for
simultaneously assessing both conflicting objectives and investigate relations
to commonly used performance indicators, both theoretically and empirically. Next
to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV
measure is used as a core concept within the construction of per-instance algorithm
selection models offering interesting insights into complementary behavior of
inexact TSP solvers.
author:
- first_name: Jakob
full_name: Bossek, Jakob
last_name: Bossek
- 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
citation:
ama: Bossek J, Kerschke P, Trautmann H. A multi-objective perspective on performance
assessment and automated selection of single-objective optimization algorithms.
Applied Soft Computing. 2020;88:105901. doi:https://doi.org/10.1016/j.asoc.2019.105901
apa: Bossek, J., Kerschke, P., & Trautmann, H. (2020). A multi-objective perspective
on performance assessment and automated selection of single-objective optimization
algorithms. Applied Soft Computing, 88, 105901. https://doi.org/10.1016/j.asoc.2019.105901
bibtex: '@article{Bossek_Kerschke_Trautmann_2020, title={A multi-objective perspective
on performance assessment and automated selection of single-objective optimization
algorithms}, volume={88}, DOI={https://doi.org/10.1016/j.asoc.2019.105901},
journal={Applied Soft Computing}, author={Bossek, Jakob and Kerschke, Pascal and
Trautmann, Heike}, year={2020}, pages={105901} }'
chicago: 'Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective
Perspective on Performance Assessment and Automated Selection of Single-Objective
Optimization Algorithms.” Applied Soft Computing 88 (2020): 105901. https://doi.org/10.1016/j.asoc.2019.105901.'
ieee: 'J. Bossek, P. Kerschke, and H. Trautmann, “A multi-objective perspective
on performance assessment and automated selection of single-objective optimization
algorithms,” Applied Soft Computing, vol. 88, p. 105901, 2020, doi: https://doi.org/10.1016/j.asoc.2019.105901.'
mla: Bossek, Jakob, et al. “A Multi-Objective Perspective on Performance Assessment
and Automated Selection of Single-Objective Optimization Algorithms.” Applied
Soft Computing, vol. 88, 2020, p. 105901, doi:https://doi.org/10.1016/j.asoc.2019.105901.
short: J. Bossek, P. Kerschke, H. Trautmann, Applied Soft Computing 88 (2020) 105901.
date_created: 2023-08-04T07:42:26Z
date_updated: 2023-10-16T13:07:59Z
department:
- _id: '34'
- _id: '819'
doi: https://doi.org/10.1016/j.asoc.2019.105901
intvolume: ' 88'
keyword:
- Algorithm selection
- Multi-objective optimization
- Performance measurement
- Combinatorial optimization
- Traveling Salesperson Problem
language:
- iso: eng
page: '105901'
publication: Applied Soft Computing
publication_identifier:
issn:
- 1568-4946
status: public
title: A multi-objective perspective on performance assessment and automated selection
of single-objective optimization algorithms
type: journal_article
user_id: '15504'
volume: 88
year: '2020'
...
---
_id: '48847'
abstract:
- lang: eng
text: Dynamic optimization problems have gained significant attention in evolutionary
computation as evolutionary algorithms (EAs) can easily adapt to changing environments.
We show that EAs can solve the graph coloring problem for bipartite graphs more
efficiently by using dynamic optimization. In our approach the graph instance
is given incrementally such that the EA can reoptimize its coloring when a new
edge introduces a conflict. We show that, when edges are inserted in a way that
preserves graph connectivity, Randomized Local Search (RLS) efficiently finds
a proper 2-coloring for all bipartite graphs. This includes graphs for which RLS
and other EAs need exponential expected time in a static optimization scenario.
We investigate different ways of building up the graph by popular graph traversals
such as breadth-first-search and depth-first-search and analyse the resulting
runtime behavior. We further show that offspring populations (e. g. a (1 + {$\lambda$})
RLS) lead to an exponential speedup in {$\lambda$}. Finally, an island model using
3 islands succeeds in an optimal time of {$\Theta$}(m) on every m-edge bipartite
graph, outperforming offspring populations. This is the first example where an
island model guarantees a speedup that is not bounded in the number of islands.
author:
- 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
- first_name: Pan
full_name: Peng, Pan
last_name: Peng
- first_name: Dirk
full_name: Sudholt, Dirk
last_name: Sudholt
citation:
ama: 'Bossek J, Neumann F, Peng P, Sudholt D. More Effective Randomized Search Heuristics
for Graph Coloring through Dynamic Optimization. In: Proceedings of the Genetic
and Evolutionary Computation Conference. GECCO ’20. Association for Computing
Machinery; 2020:1277–1285. doi:10.1145/3377930.3390174'
apa: Bossek, J., Neumann, F., Peng, P., & Sudholt, D. (2020). More Effective
Randomized Search Heuristics for Graph Coloring through Dynamic Optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 1277–1285.
https://doi.org/10.1145/3377930.3390174
bibtex: '@inproceedings{Bossek_Neumann_Peng_Sudholt_2020, place={New York, NY, USA},
series={GECCO ’20}, title={More Effective Randomized Search Heuristics for Graph
Coloring through Dynamic Optimization}, DOI={10.1145/3377930.3390174},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Neumann,
Frank and Peng, Pan and Sudholt, Dirk}, year={2020}, pages={1277–1285}, collection={GECCO
’20} }'
chicago: 'Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “More Effective
Randomized Search Heuristics for Graph Coloring through Dynamic Optimization.”
In Proceedings of the Genetic and Evolutionary Computation Conference,
1277–1285. GECCO ’20. New York, NY, USA: Association for Computing Machinery,
2020. https://doi.org/10.1145/3377930.3390174.'
ieee: 'J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “More Effective Randomized
Search Heuristics for Graph Coloring through Dynamic Optimization,” in Proceedings
of the Genetic and Evolutionary Computation Conference, 2020, pp. 1277–1285,
doi: 10.1145/3377930.3390174.'
mla: Bossek, Jakob, et al. “More Effective Randomized Search Heuristics for Graph
Coloring through Dynamic Optimization.” Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, 2020, pp. 1277–1285,
doi:10.1145/3377930.3390174.
short: 'J. Bossek, F. Neumann, P. Peng, D. Sudholt, in: Proceedings of the Genetic
and Evolutionary Computation Conference, Association for Computing Machinery,
New York, NY, USA, 2020, pp. 1277–1285.'
date_created: 2023-11-14T15:58:53Z
date_updated: 2023-12-13T10:43:41Z
department:
- _id: '819'
doi: 10.1145/3377930.3390174
extern: '1'
keyword:
- dynamic optimization
- evolutionary algorithms
- running time analysis
- theory
language:
- iso: eng
page: 1277–1285
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-7128-5
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO ’20
status: public
title: More Effective Randomized Search Heuristics for Graph Coloring through Dynamic
Optimization
type: conference
user_id: '102979'
year: '2020'
...
---
_id: '48849'
abstract:
- lang: eng
text: One-shot optimization tasks require to determine the set of solution candidates
prior to their evaluation, i.e., without possibility for adaptive sampling. We
consider two variants, classic one-shot optimization (where our aim is to find
at least one solution of high quality) and one-shot regression (where the goal
is to fit a model that resembles the true problem as well as possible). For both
tasks it seems intuitive that well-distributed samples should perform better than
uniform or grid-based samples, since they show a better coverage of the decision
space. In practice, quasi-random designs such as Latin Hypercube Samples and low-discrepancy
point sets are indeed very commonly used designs for one-shot optimization tasks.
We study in this work how well low star discrepancy correlates with performance
in one-shot optimization. Our results confirm an advantage of low-discrepancy
designs, but also indicate the correlation between discrepancy values and overall
performance is rather weak. We then demonstrate that commonly used designs may
be far from optimal. More precisely, we evolve 24 very specific designs that each
achieve good performance on one of our benchmark problems. Interestingly, we find
that these specifically designed samples yield surprisingly good performance across
the whole benchmark set. Our results therefore give strong indication that significant
performance gains over state-of-the-art one-shot sampling techniques are possible,
and that evolutionary algorithms can be an efficient means to evolve these.
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Carola
full_name: Doerr, Carola
last_name: Doerr
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Aneta
full_name: Neumann, Aneta
last_name: Neumann
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Bossek J, Doerr C, Kerschke P, Neumann A, Neumann F. Evolving Sampling Strategies
for One-Shot Optimization Tasks. In: Parallel Problem Solving from Nature (PPSN
XVI). Springer-Verlag; 2020:111–124. doi:10.1007/978-3-030-58112-1_8'
apa: Bossek, J., Doerr, C., Kerschke, P., Neumann, A., & Neumann, F. (2020).
Evolving Sampling Strategies for One-Shot Optimization Tasks. Parallel Problem
Solving from Nature (PPSN XVI), 111–124. https://doi.org/10.1007/978-3-030-58112-1_8
bibtex: '@inproceedings{Bossek_Doerr_Kerschke_Neumann_Neumann_2020, place={Berlin,
Heidelberg}, title={Evolving Sampling Strategies for One-Shot Optimization Tasks},
DOI={10.1007/978-3-030-58112-1_8},
booktitle={Parallel Problem Solving from Nature (PPSN XVI)}, publisher={Springer-Verlag},
author={Bossek, Jakob and Doerr, Carola and Kerschke, Pascal and Neumann, Aneta
and Neumann, Frank}, year={2020}, pages={111–124} }'
chicago: 'Bossek, Jakob, Carola Doerr, Pascal Kerschke, Aneta Neumann, and Frank
Neumann. “Evolving Sampling Strategies for One-Shot Optimization Tasks.” In Parallel
Problem Solving from Nature (PPSN XVI), 111–124. Berlin, Heidelberg: Springer-Verlag,
2020. https://doi.org/10.1007/978-3-030-58112-1_8.'
ieee: 'J. Bossek, C. Doerr, P. Kerschke, A. Neumann, and F. Neumann, “Evolving Sampling
Strategies for One-Shot Optimization Tasks,” in Parallel Problem Solving from
Nature (PPSN XVI), 2020, pp. 111–124, doi: 10.1007/978-3-030-58112-1_8.'
mla: Bossek, Jakob, et al. “Evolving Sampling Strategies for One-Shot Optimization
Tasks.” Parallel Problem Solving from Nature (PPSN XVI), Springer-Verlag,
2020, pp. 111–124, doi:10.1007/978-3-030-58112-1_8.
short: 'J. Bossek, C. Doerr, P. Kerschke, A. Neumann, F. Neumann, in: Parallel Problem
Solving from Nature (PPSN XVI), Springer-Verlag, Berlin, Heidelberg, 2020, pp.
111–124.'
date_created: 2023-11-14T15:58:53Z
date_updated: 2023-12-13T10:43:53Z
department:
- _id: '819'
doi: 10.1007/978-3-030-58112-1_8
extern: '1'
keyword:
- Continuous optimization
- Fully parallel search
- One-shot optimization
- Regression
- Surrogate-assisted optimization
language:
- iso: eng
page: 111–124
place: Berlin, Heidelberg
publication: Parallel Problem Solving from Nature (PPSN XVI)
publication_identifier:
isbn:
- 978-3-030-58111-4
publication_status: published
publisher: Springer-Verlag
status: public
title: Evolving Sampling Strategies for One-Shot Optimization Tasks
type: conference
user_id: '102979'
year: '2020'
...
---
_id: '48851'
abstract:
- lang: eng
text: Several important optimization problems in the area of vehicle routing can
be seen as variants of the classical Traveling Salesperson Problem (TSP). In the
area of evolutionary computation, the Traveling Thief Problem (TTP) has gained
increasing interest over the last 5 years. In this paper, we investigate the effect
of weights on such problems, in the sense that the cost of traveling increases
with respect to the weights of nodes already visited during a tour. This provides
abstractions of important TSP variants such as the Traveling Thief Problem and
time dependent TSP variants, and allows to study precisely the increase in difficulty
caused by weight dependence. We provide a 3.59-approximation for this weight dependent
version of TSP with metric distances and bounded positive weights. Furthermore,
we conduct experimental investigations for simple randomized local search with
classical mutation operators and two variants of the state-of-the-art evolutionary
algorithm EAX adapted to the weighted TSP. Our results show the impact of the
node weights on the position of the nodes in the resulting tour.
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Katrin
full_name: Casel, Katrin
last_name: Casel
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Bossek J, Casel K, Kerschke P, Neumann F. The Node Weight Dependent Traveling
Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics.
In: Proceedings of the Genetic and Evolutionary Computation Conference.
GECCO ’20. Association for Computing Machinery; 2020:1286–1294. doi:10.1145/3377930.3390243'
apa: 'Bossek, J., Casel, K., Kerschke, P., & Neumann, F. (2020). The Node Weight
Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized
Search Heuristics. Proceedings of the Genetic and Evolutionary Computation
Conference, 1286–1294. https://doi.org/10.1145/3377930.3390243'
bibtex: '@inproceedings{Bossek_Casel_Kerschke_Neumann_2020, place={New York, NY,
USA}, series={GECCO ’20}, title={The Node Weight Dependent Traveling Salesperson
Problem: Approximation Algorithms and Randomized Search Heuristics}, DOI={10.1145/3377930.3390243},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Casel,
Katrin and Kerschke, Pascal and Neumann, Frank}, year={2020}, pages={1286–1294},
collection={GECCO ’20} }'
chicago: 'Bossek, Jakob, Katrin Casel, Pascal Kerschke, and Frank Neumann. “The
Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms
and Randomized Search Heuristics.” In Proceedings of the Genetic and Evolutionary
Computation Conference, 1286–1294. GECCO ’20. New York, NY, USA: Association
for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390243.'
ieee: 'J. Bossek, K. Casel, P. Kerschke, and F. Neumann, “The Node Weight Dependent
Traveling Salesperson Problem: Approximation Algorithms and Randomized Search
Heuristics,” in Proceedings of the Genetic and Evolutionary Computation Conference,
2020, pp. 1286–1294, doi: 10.1145/3377930.3390243.'
mla: 'Bossek, Jakob, et al. “The Node Weight Dependent Traveling Salesperson Problem:
Approximation Algorithms and Randomized Search Heuristics.” Proceedings of
the Genetic and Evolutionary Computation Conference, Association for Computing
Machinery, 2020, pp. 1286–1294, doi:10.1145/3377930.3390243.'
short: 'J. Bossek, K. Casel, P. Kerschke, F. Neumann, in: Proceedings of the Genetic
and Evolutionary Computation Conference, Association for Computing Machinery,
New York, NY, USA, 2020, pp. 1286–1294.'
date_created: 2023-11-14T15:58:53Z
date_updated: 2023-12-13T10:43:33Z
department:
- _id: '819'
doi: 10.1145/3377930.3390243
extern: '1'
keyword:
- dynamic optimization
- evolutionary algorithms
- running time analysis
- theory
language:
- iso: eng
page: 1286–1294
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-7128-5
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO ’20
status: public
title: 'The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms
and Randomized Search Heuristics'
type: conference
user_id: '102979'
year: '2020'
...
---
_id: '48845'
abstract:
- lang: eng
text: In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Problems
(VRPs) often imply repeated decision making on dynamic customer requests. As in
classical VRPs, tours have to be planned short while the number of serviced customers
has to be maximized at the same time resulting in a multi-objective problem. Beyond
that, however, dynamic requests lead to the need for re-planning of not yet realized
tour parts, while already realized tour parts are irreversible. In this paper
we study this type of bi-objective dynamic VRP including sequential decision making
and concurrent realization of decisions. We adopt a recently proposed Dynamic
Evolutionary Multi-Objective Algorithm (DEMOA) for a related VRP problem and extend
it to the more realistic (here considered) scenario of multiple vehicles. We empirically
show that our DEMOA is competitive with a multi-vehicle offline and clairvoyant
variant of the proposed DEMOA as well as with the dynamic single-vehicle approach
proposed earlier.
author:
- 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
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Bossek J, Grimme C, Trautmann H. Dynamic Bi-Objective Routing of Multiple
Vehicles. In: Proceedings of the Genetic and Evolutionary Computation Conference.
GECCO ’20. Association for Computing Machinery; 2020:166–174. doi:10.1145/3377930.3390146'
apa: Bossek, J., Grimme, C., & Trautmann, H. (2020). Dynamic Bi-Objective Routing
of Multiple Vehicles. Proceedings of the Genetic and Evolutionary Computation
Conference, 166–174. https://doi.org/10.1145/3377930.3390146
bibtex: '@inproceedings{Bossek_Grimme_Trautmann_2020, place={New York, NY, USA},
series={GECCO ’20}, title={Dynamic Bi-Objective Routing of Multiple Vehicles},
DOI={10.1145/3377930.3390146},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Grimme,
Christian and Trautmann, Heike}, year={2020}, pages={166–174}, collection={GECCO
’20} }'
chicago: 'Bossek, Jakob, Christian Grimme, and Heike Trautmann. “Dynamic Bi-Objective
Routing of Multiple Vehicles.” In Proceedings of the Genetic and Evolutionary
Computation Conference, 166–174. GECCO ’20. New York, NY, USA: Association
for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390146.'
ieee: 'J. Bossek, C. Grimme, and H. Trautmann, “Dynamic Bi-Objective Routing of
Multiple Vehicles,” in Proceedings of the Genetic and Evolutionary Computation
Conference, 2020, pp. 166–174, doi: 10.1145/3377930.3390146.'
mla: Bossek, Jakob, et al. “Dynamic Bi-Objective Routing of Multiple Vehicles.”
Proceedings of the Genetic and Evolutionary Computation Conference, Association
for Computing Machinery, 2020, pp. 166–174, doi:10.1145/3377930.3390146.
short: 'J. Bossek, C. Grimme, H. Trautmann, in: Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, New York, NY, USA,
2020, pp. 166–174.'
date_created: 2023-11-14T15:58:52Z
date_updated: 2023-12-13T10:43:24Z
department:
- _id: '819'
doi: 10.1145/3377930.3390146
extern: '1'
keyword:
- decision making
- dynamic optimization
- evolutionary algorithms
- multi-objective optimization
- vehicle routing
language:
- iso: eng
page: 166–174
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-7128-5
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO ’20
status: public
title: Dynamic Bi-Objective Routing of Multiple Vehicles
type: conference
user_id: '102979'
year: '2020'
...
---
_id: '48850'
abstract:
- lang: eng
text: Sequential model-based optimization (SMBO) approaches are algorithms for solving
problems that require computationally or otherwise expensive function evaluations.
The key design principle of SMBO is a substitution of the true objective function
by a surrogate, which is used to propose the point(s) to be evaluated next. SMBO
algorithms are intrinsically modular, leaving the user with many important design
choices. Significant research efforts go into understanding which settings perform
best for which type of problems. Most works, however, focus on the choice of the
model, the acquisition function, and the strategy used to optimize the latter.
The choice of the initial sampling strategy, however, receives much less attention.
Not surprisingly, quite diverging recommendations can be found in the literature.
We analyze in this work how the size and the distribution of the initial sample
influences the overall quality of the efficient global optimization (EGO) algorithm,
a well-known SMBO approach. While, overall, small initial budgets using Halton
sampling seem preferable, we also observe that the performance landscape is rather
unstructured. We furthermore identify several situations in which EGO performs
unfavorably against random sampling. Both observations indicate that an adaptive
SMBO design could be beneficial, making SMBO an interesting test-bed for automated
algorithm design.
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Carola
full_name: Doerr, Carola
last_name: Doerr
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
citation:
ama: 'Bossek J, Doerr C, Kerschke P. Initial Design Strategies and Their Effects
on Sequential Model-Based Optimization: An Exploratory Case Study Based on BBOB.
In: Proceedings of the Genetic and Evolutionary Computation Conference.
GECCO ’20. Association for Computing Machinery; 2020:778–786. doi:10.1145/3377930.3390155'
apa: 'Bossek, J., Doerr, C., & Kerschke, P. (2020). Initial Design Strategies
and Their Effects on Sequential Model-Based Optimization: An Exploratory Case
Study Based on BBOB. Proceedings of the Genetic and Evolutionary Computation
Conference, 778–786. https://doi.org/10.1145/3377930.3390155'
bibtex: '@inproceedings{Bossek_Doerr_Kerschke_2020, place={New York, NY, USA}, series={GECCO
’20}, title={Initial Design Strategies and Their Effects on Sequential Model-Based
Optimization: An Exploratory Case Study Based on BBOB}, DOI={10.1145/3377930.3390155},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Doerr,
Carola and Kerschke, Pascal}, year={2020}, pages={778–786}, collection={GECCO
’20} }'
chicago: 'Bossek, Jakob, Carola Doerr, and Pascal Kerschke. “Initial Design Strategies
and Their Effects on Sequential Model-Based Optimization: An Exploratory Case
Study Based on BBOB.” In Proceedings of the Genetic and Evolutionary Computation
Conference, 778–786. GECCO ’20. New York, NY, USA: Association for Computing
Machinery, 2020. https://doi.org/10.1145/3377930.3390155.'
ieee: 'J. Bossek, C. Doerr, and P. Kerschke, “Initial Design Strategies and Their
Effects on Sequential Model-Based Optimization: An Exploratory Case Study Based
on BBOB,” in Proceedings of the Genetic and Evolutionary Computation Conference,
2020, pp. 778–786, doi: 10.1145/3377930.3390155.'
mla: 'Bossek, Jakob, et al. “Initial Design Strategies and Their Effects on Sequential
Model-Based Optimization: An Exploratory Case Study Based on BBOB.” Proceedings
of the Genetic and Evolutionary Computation Conference, Association for Computing
Machinery, 2020, pp. 778–786, doi:10.1145/3377930.3390155.'
short: 'J. Bossek, C. Doerr, P. Kerschke, in: Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, New York, NY, USA,
2020, pp. 778–786.'
date_created: 2023-11-14T15:58:53Z
date_updated: 2023-12-13T10:44:01Z
department:
- _id: '819'
doi: 10.1145/3377930.3390155
extern: '1'
keyword:
- continuous black-box optimization
- design of experiments
- initial design
- sequential model-based optimization
language:
- iso: eng
page: 778–786
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-7128-5
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO ’20
status: public
title: 'Initial Design Strategies and Their Effects on Sequential Model-Based Optimization:
An Exploratory Case Study Based on BBOB'
type: conference
user_id: '102979'
year: '2020'
...
---
_id: '48848'
abstract:
- lang: eng
text: We build upon a recently proposed multi-objective view onto performance measurement
of single-objective stochastic solvers. The trade-off between the fraction of
failed runs and the mean runtime of successful runs \textendash both to be minimized
\textendash is directly analyzed based on a study on algorithm selection of inexact
state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover,
we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization
for simultaneously assessing both conflicting objectives and investigate relations
to commonly used performance indicators, both theoretically and empirically. Next
to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV
measure is used as a core concept within the construction of per-instance algorithm
selection models offering interesting insights into complementary behavior of
inexact TSP solvers. \textbullet The multi-objective perspective is naturally
generalizable to multiple objectives. \textbullet Proof of relationship between
HV and the PAR in the considered bi-objective space. \textbullet New insights
into complementary behavior of stochastic optimization algorithms.
author:
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: Bossek J, Kerschke P, Trautmann H. A Multi-Objective Perspective on Performance
Assessment and Automated Selection of Single-Objective Optimization Algorithms.
Applied Soft Computing. 2020;88(C). doi:10.1016/j.asoc.2019.105901
apa: Bossek, J., Kerschke, P., & Trautmann, H. (2020). A Multi-Objective Perspective
on Performance Assessment and Automated Selection of Single-Objective Optimization
Algorithms. Applied Soft Computing, 88(C). https://doi.org/10.1016/j.asoc.2019.105901
bibtex: '@article{Bossek_Kerschke_Trautmann_2020, title={A Multi-Objective Perspective
on Performance Assessment and Automated Selection of Single-Objective Optimization
Algorithms}, volume={88}, DOI={10.1016/j.asoc.2019.105901},
number={C}, journal={Applied Soft Computing}, author={Bossek, Jakob and Kerschke,
Pascal and Trautmann, Heike}, year={2020} }'
chicago: Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective
Perspective on Performance Assessment and Automated Selection of Single-Objective
Optimization Algorithms.” Applied Soft Computing 88, no. C (2020). https://doi.org/10.1016/j.asoc.2019.105901.
ieee: 'J. Bossek, P. Kerschke, and H. Trautmann, “A Multi-Objective Perspective
on Performance Assessment and Automated Selection of Single-Objective Optimization
Algorithms,” Applied Soft Computing, vol. 88, no. C, 2020, doi: 10.1016/j.asoc.2019.105901.'
mla: Bossek, Jakob, et al. “A Multi-Objective Perspective on Performance Assessment
and Automated Selection of Single-Objective Optimization Algorithms.” Applied
Soft Computing, vol. 88, no. C, 2020, doi:10.1016/j.asoc.2019.105901.
short: J. Bossek, P. Kerschke, H. Trautmann, Applied Soft Computing 88 (2020).
date_created: 2023-11-14T15:58:53Z
date_updated: 2023-12-13T10:52:17Z
department:
- _id: '819'
doi: 10.1016/j.asoc.2019.105901
intvolume: ' 88'
issue: C
keyword:
- Algorithm selection
- Combinatorial optimization
- Multi-objective optimization
- Performance measurement
- Traveling Salesperson Problem
language:
- iso: eng
publication: Applied Soft Computing
publication_identifier:
issn:
- 1568-4946
status: public
title: A Multi-Objective Perspective on Performance Assessment and Automated Selection
of Single-Objective Optimization Algorithms
type: journal_article
user_id: '102979'
volume: 88
year: '2020'
...
---
_id: '4562'
abstract:
- lang: eng
text: Employing main and sector-specific investment-grade CDS indices from the North
American and European CDS market and performing mean-variance out-of-sample analyses
for conservative and aggressive investors over the period from 2006 to 2014, this
paper analyzes portfolio benefits of adding corporate CDS indices to a traditional
financial portfolio consisting of stock and sovereign bond indices. As a baseline
result, we initially find an increase in portfolio (downside) risk-diversification
when adding CDS indices, which is observed irrespective of both CDS markets, investor-types
and different sub-periods, including the global financial crisis and European
sovereign debt crisis. In addition, the analysis reveals higher portfolio excess
returns and performance in CDS index portfolios, however, these effects clearly
differ between markets, investor-types and sub-periods. Overall, portfolio benefits
of adding CDS indices mainly result from the fact that institutional investors
replace sovereign bond indices rather than stock indices by CDS indices due to
better risk-return characteristics. Our baseline findings remain robust under
a variety of robustness checks. Results from sensitivity analyses provide further
important implications for institutional investors with a strategic focus on a
long-term conservative portfolio management.
article_type: original
author:
- first_name: Benjamin
full_name: Hippert, Benjamin
id: '48476'
last_name: Hippert
- first_name: André
full_name: Uhde, André
id: '36049'
last_name: Uhde
orcid: https://orcid.org/0000-0002-8058-8857
- first_name: Sascha Tobias
full_name: Wengerek, Sascha Tobias
id: '48837'
last_name: Wengerek
orcid: 0000-0002-7820-3903
citation:
ama: 'Hippert B, Uhde A, Wengerek ST. Portfolio Benefits of Adding Corporate Credit
Default Swap Indices: Evidence from North America and Europe. Review of Derivatives
Research . 2019;22(2):203-259. doi:https://doi.org/10.1007/s11147-018-9148-8'
apa: 'Hippert, B., Uhde, A., & Wengerek, S. T. (2019). Portfolio Benefits of
Adding Corporate Credit Default Swap Indices: Evidence from North America and
Europe. Review of Derivatives Research , 22(2), 203–259. https://doi.org/10.1007/s11147-018-9148-8'
bibtex: '@article{Hippert_Uhde_Wengerek_2019, title={Portfolio Benefits of Adding
Corporate Credit Default Swap Indices: Evidence from North America and Europe},
volume={22}, DOI={https://doi.org/10.1007/s11147-018-9148-8},
number={2}, journal={Review of Derivatives Research }, author={Hippert, Benjamin
and Uhde, André and Wengerek, Sascha Tobias}, year={2019}, pages={203–259} }'
chicago: 'Hippert, Benjamin, André Uhde, and Sascha Tobias Wengerek. “Portfolio
Benefits of Adding Corporate Credit Default Swap Indices: Evidence from North
America and Europe.” Review of Derivatives Research 22, no. 2 (2019):
203–59. https://doi.org/10.1007/s11147-018-9148-8.'
ieee: 'B. Hippert, A. Uhde, and S. T. Wengerek, “Portfolio Benefits of Adding Corporate
Credit Default Swap Indices: Evidence from North America and Europe,” Review
of Derivatives Research , vol. 22, no. 2, pp. 203–259, 2019, doi: https://doi.org/10.1007/s11147-018-9148-8.'
mla: 'Hippert, Benjamin, et al. “Portfolio Benefits of Adding Corporate Credit Default
Swap Indices: Evidence from North America and Europe.” Review of Derivatives
Research , vol. 22, no. 2, 2019, pp. 203–59, doi:https://doi.org/10.1007/s11147-018-9148-8.'
short: B. Hippert, A. Uhde, S.T. Wengerek, Review of Derivatives Research 22 (2019)
203–259.
date_created: 2018-10-01T12:17:35Z
date_updated: 2022-05-04T06:15:02Z
department:
- _id: '188'
- _id: '186'
doi: https://doi.org/10.1007/s11147-018-9148-8
intvolume: ' 22'
issue: '2'
jel:
- C61
- G01
- G11
- G15
- G23
keyword:
- Corporate credit default swap indices
- Mean-variance asset allocation
- Out-of-sample portfolio optimization
- Portfolio risk-diversification
- Portfolio performance evaluation
language:
- iso: eng
page: 203-259
publication: 'Review of Derivatives Research '
publication_status: published
status: public
title: 'Portfolio Benefits of Adding Corporate Credit Default Swap Indices: Evidence
from North America and Europe'
type: journal_article
user_id: '36049'
volume: 22
year: '2019'
...
---
_id: '10000'
abstract:
- lang: eng
text: Ultraschall wird zur Effizienzsteigerung in verfahrenstechnischen Prozessen
eingesetzt. Die Betriebsparamter der Ultraschallsysteme werden empirisch ermittelt,
da derzeit keine systematische Analyse der Wechselwirkung zwischen Ultraschallwandler
und Schallfeld sowie kein Verfahren zur Messung der Kavitationsaktivität ohne
zusätzlichen Sensor existieren. Auf Basis einer experimentellen Analyse des betrachteten
sonochemischen Reaktors wird ein Finite-Elemente-Modell aufgebaut, das die Wechselwirkung
zwischen Schallfeld und Ultraschallwandler berücksichtigt. Die modellbasierte
Analyse zeigt, dass wegen der akustischen Eigenschaften des Autoklavs nur direkt
an der Sonotrode Kavitation entsteht. Die Wechselwirkung zwischen Ultraschallwandler
und Schallfeld ermöglicht Aussagen über das Schallfeld und die Kavitationsaktivität
auf Basis der Rückwirkung auf den Ultraschallwandler. Die lineare Schalldruckverteilung
ermöglicht eine Prognose über die Verteilung von Kavitationszonen. Das beschriebene
Modell liefert wertvolle Erkenntnisse für die Auslegung, Analyse und Skalierung
sonochemischer Reaktoren. Auf Grund der rauen Prozessrandbedingungen ist die Applikation
von Sensoren zur Überwachung der Kavitationsaktivität in vielen sonochemischen
Prozessen nicht möglich. Zur prozessbegleitenden Messung der Kavitationsaktivität
wird ein Verfahren entwickelt, das die Bewertung der Kavitationsaktivität durch
Auswertung der Rückwirkung auf den Ultraschallwandler erlaubt. Das Messverfahren
ermöglicht eine vorhersagbare und reproduzierbare Durchführung kavitationsbasierter
Prozesse und stellt eine wichtige Erweiterung für bestehende und neue Ultraschallsysteme
dar.
author:
- first_name: Peter
full_name: Bornmann, Peter
last_name: Bornmann
citation:
ama: Bornmann P. Modellierung Und Experimentelle Charakterisierung Der Wechselwirkung
Zwischen Ultraschallwandler Und Flüssigkeit in Kavitationsbasierten Prozessen.
Shaker; 2019.
apa: Bornmann, P. (2019). Modellierung und experimentelle Charakterisierung der
Wechselwirkung zwischen Ultraschallwandler und Flüssigkeit in kavitationsbasierten
Prozessen. Shaker.
bibtex: '@book{Bornmann_2019, title={Modellierung und experimentelle Charakterisierung
der Wechselwirkung zwischen Ultraschallwandler und Flüssigkeit in kavitationsbasierten
Prozessen}, publisher={Shaker}, author={Bornmann, Peter}, year={2019} }'
chicago: Bornmann, Peter. Modellierung Und Experimentelle Charakterisierung Der
Wechselwirkung Zwischen Ultraschallwandler Und Flüssigkeit in Kavitationsbasierten
Prozessen. Shaker, 2019.
ieee: P. Bornmann, Modellierung und experimentelle Charakterisierung der Wechselwirkung
zwischen Ultraschallwandler und Flüssigkeit in kavitationsbasierten Prozessen.
Shaker, 2019.
mla: Bornmann, Peter. Modellierung Und Experimentelle Charakterisierung Der Wechselwirkung
Zwischen Ultraschallwandler Und Flüssigkeit in Kavitationsbasierten Prozessen.
Shaker, 2019.
short: P. Bornmann, Modellierung Und Experimentelle Charakterisierung Der Wechselwirkung
Zwischen Ultraschallwandler Und Flüssigkeit in Kavitationsbasierten Prozessen,
Shaker, 2019.
date_created: 2019-05-27T10:29:53Z
date_updated: 2023-09-15T12:23:55Z
department:
- _id: '151'
keyword:
- Sonochemie
- Akustische Kavitation
- Kavitationsmessung
- Kavitationsdetektion
- FEM-Simulation Ultraschallwandler
- Prozessüberwachung
- FEM-Simulation Schallfeld
- Self-Sensing
- Piezoelektrische Ultraschallwandler
- Ultraschallreinigung
language:
- iso: eng
publisher: Shaker
status: public
title: Modellierung und experimentelle Charakterisierung der Wechselwirkung zwischen
Ultraschallwandler und Flüssigkeit in kavitationsbasierten Prozessen
type: dissertation
user_id: '210'
year: '2019'
...