---
_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: '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: '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: '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: '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: '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: '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
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
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: 2024-06-10T12:00:46Z
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: '48841'
abstract:
- lang: eng
text: We tackle a bi-objective dynamic orienteering problem where customer requests
arise as time passes by. The goal is to minimize the tour length traveled by a
single delivery vehicle while simultaneously keeping the number of dismissed dynamic
customers to a minimum. We propose a dynamic Evolutionary Multi-Objective Algorithm
which is grounded on insights gained from a previous series of work on an a-posteriori
version of the problem, where all request times are known in advance. In our experiments,
we simulate different decision maker strategies and evaluate the development of
the Pareto-front approximations on exemplary problem instances. It turns out,
that despite severely reduced computational budget and no oracle-knowledge of
request times the dynamic EMOA is capable of producing approximations which partially
dominate the results of the a-posteriori EMOA and dynamic integer linear programming
strategies.
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: Stephan
full_name: Meisel, Stephan
last_name: Meisel
- first_name: Günter
full_name: Rudolph, Günter
last_name: Rudolph
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Bossek J, Grimme C, Meisel S, Rudolph G, Trautmann H. Bi-Objective Orienteering:
Towards a Dynamic Multi-objective Evolutionary Algorithm. In: Deb K, Goodman E,
Coello Coello CA, et al., eds. Evolutionary Multi-Criterion Optimization (EMO).
Lecture Notes in Computer Science. Springer International Publishing; 2019:516–528.
doi:10.1007/978-3-030-12598-1_41'
apa: 'Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2019).
Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm.
In K. Deb, E. Goodman, C. A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim,
& P. Reed (Eds.), Evolutionary Multi-Criterion Optimization (EMO) (pp.
516–528). Springer International Publishing. https://doi.org/10.1007/978-3-030-12598-1_41'
bibtex: '@inproceedings{Bossek_Grimme_Meisel_Rudolph_Trautmann_2019, place={Cham},
series={Lecture Notes in Computer Science}, title={Bi-Objective Orienteering:
Towards a Dynamic Multi-objective Evolutionary Algorithm}, DOI={10.1007/978-3-030-12598-1_41},
booktitle={Evolutionary Multi-Criterion Optimization (EMO)}, publisher={Springer
International Publishing}, author={Bossek, Jakob and Grimme, Christian and Meisel,
Stephan and Rudolph, Günter and Trautmann, Heike}, editor={Deb, Kalyanmoy and
Goodman, Erik and Coello Coello, Carlos A. and Klamroth, Kathrin and Miettinen,
Kaisa and Mostaghim, Sanaz and Reed, Patrick}, year={2019}, pages={516–528}, collection={Lecture
Notes in Computer Science} }'
chicago: 'Bossek, Jakob, Christian Grimme, Stephan Meisel, Günter Rudolph, and Heike
Trautmann. “Bi-Objective Orienteering: Towards a Dynamic Multi-Objective Evolutionary
Algorithm.” In Evolutionary Multi-Criterion Optimization (EMO), edited
by Kalyanmoy Deb, Erik Goodman, Carlos A. Coello Coello, Kathrin Klamroth, Kaisa
Miettinen, Sanaz Mostaghim, and Patrick Reed, 516–528. Lecture Notes in Computer
Science. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-12598-1_41.'
ieee: 'J. Bossek, C. Grimme, S. Meisel, G. Rudolph, and H. Trautmann, “Bi-Objective
Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm,” in Evolutionary
Multi-Criterion Optimization (EMO), 2019, pp. 516–528, doi: 10.1007/978-3-030-12598-1_41.'
mla: 'Bossek, Jakob, et al. “Bi-Objective Orienteering: Towards a Dynamic Multi-Objective
Evolutionary Algorithm.” Evolutionary Multi-Criterion Optimization (EMO),
edited by Kalyanmoy Deb et al., Springer International Publishing, 2019, pp. 516–528,
doi:10.1007/978-3-030-12598-1_41.'
short: 'J. Bossek, C. Grimme, S. Meisel, G. Rudolph, H. Trautmann, in: K. Deb, E.
Goodman, C.A. Coello Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed
(Eds.), Evolutionary Multi-Criterion Optimization (EMO), Springer International
Publishing, Cham, 2019, pp. 516–528.'
date_created: 2023-11-14T15:58:52Z
date_updated: 2023-12-13T10:43:07Z
department:
- _id: '819'
doi: 10.1007/978-3-030-12598-1_41
editor:
- first_name: Kalyanmoy
full_name: Deb, Kalyanmoy
last_name: Deb
- first_name: Erik
full_name: Goodman, Erik
last_name: Goodman
- first_name: Carlos A.
full_name: Coello Coello, Carlos A.
last_name: Coello Coello
- first_name: Kathrin
full_name: Klamroth, Kathrin
last_name: Klamroth
- first_name: Kaisa
full_name: Miettinen, Kaisa
last_name: Miettinen
- first_name: Sanaz
full_name: Mostaghim, Sanaz
last_name: Mostaghim
- first_name: Patrick
full_name: Reed, Patrick
last_name: Reed
extern: '1'
keyword:
- Combinatorial optimization
- Dynamic optimization
- Metaheuristics
- Multi-objective optimization
- Vehicle routing
language:
- iso: eng
page: 516–528
place: Cham
publication: Evolutionary Multi-Criterion Optimization (EMO)
publication_identifier:
isbn:
- 978-3-030-12598-1
publication_status: published
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: 'Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary
Algorithm'
type: conference
user_id: '102979'
year: '2019'
...
---
_id: '48840'
abstract:
- lang: eng
text: Research has shown that for many single-objective graph problems where optimum
solutions are composed of low weight sub-graphs, such as the minimum spanning
tree problem (MST), mutation operators favoring low weight edges show superior
performance. Intuitively, similar observations should hold for multi-criteria
variants of such problems. In this work, we focus on the multi-criteria MST problem.
A thorough experimental study is conducted where we estimate the probability of
edges being part of non-dominated spanning trees as a function of the edges’ non-domination
level or domination count, respectively. Building on gained insights, we propose
several biased one-edge-exchange mutation operators that differ in the used edge-selection
probability distribution (biased towards edges of low rank). Our empirical analysis
shows that among different graph types (dense and sparse) and edge weight types
(both uniformly random and combinations of Euclidean and uniformly random) biased
edge-selection strategies perform superior in contrast to the baseline uniform
edge-selection. Our findings are in particular strong for dense graphs.
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: Frank
full_name: Neumann, Frank
last_name: Neumann
citation:
ama: 'Bossek J, Grimme C, Neumann F. On the Benefits of Biased Edge-Exchange Mutation
for the Multi-Criteria Spanning Tree Problem. In: Proceedings of the Genetic
and Evolutionary Computation Conference. GECCO ’19. Association for Computing
Machinery; 2019:516–523. doi:10.1145/3321707.3321818'
apa: Bossek, J., Grimme, C., & Neumann, F. (2019). On the Benefits of Biased
Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem. Proceedings
of the Genetic and Evolutionary Computation Conference, 516–523. https://doi.org/10.1145/3321707.3321818
bibtex: '@inproceedings{Bossek_Grimme_Neumann_2019, place={New York, NY, USA}, series={GECCO
’19}, title={On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria
Spanning Tree Problem}, DOI={10.1145/3321707.3321818},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Grimme,
Christian and Neumann, Frank}, year={2019}, pages={516–523}, collection={GECCO
’19} }'
chicago: 'Bossek, Jakob, Christian Grimme, and Frank Neumann. “On the Benefits of
Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem.” In
Proceedings of the Genetic and Evolutionary Computation Conference, 516–523.
GECCO ’19. New York, NY, USA: Association for Computing Machinery, 2019. https://doi.org/10.1145/3321707.3321818.'
ieee: 'J. Bossek, C. Grimme, and F. Neumann, “On the Benefits of Biased Edge-Exchange
Mutation for the Multi-Criteria Spanning Tree Problem,” in Proceedings of the
Genetic and Evolutionary Computation Conference, 2019, pp. 516–523, doi: 10.1145/3321707.3321818.'
mla: Bossek, Jakob, et al. “On the Benefits of Biased Edge-Exchange Mutation for
the Multi-Criteria Spanning Tree Problem.” Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, 2019, pp. 516–523,
doi:10.1145/3321707.3321818.
short: 'J. Bossek, C. Grimme, F. Neumann, in: Proceedings of the Genetic and Evolutionary
Computation Conference, Association for Computing Machinery, New York, NY, USA,
2019, pp. 516–523.'
date_created: 2023-11-14T15:58:52Z
date_updated: 2023-12-13T10:42:24Z
department:
- _id: '819'
doi: 10.1145/3321707.3321818
extern: '1'
keyword:
- biased mutation
- combinatorial optimization
- minimum spanning tree
- multi-objective optimization
language:
- iso: eng
page: 516–523
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-6111-8
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO ’19
status: public
title: On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning
Tree Problem
type: conference
user_id: '102979'
year: '2019'
...
---
_id: '9999'
abstract:
- lang: eng
text: Ultrasonic wire bonding is an indispensable process in the industrial manufacturing
of semiconductor devices. Copper wire is increasingly replacing the well-established
aluminium wire because of its superior electrical, thermal and mechanical properties.
Copper wire processes differ significantly from aluminium processes and are more
sensitive to disturbances, which reduces the range of parameter values suitable
for a stable process. Disturbances can be compensated by an adaption of process
parameters, but finding suitable parameters manually is difficult and time-consuming.
This paper presents a physical model of the ultrasonic wire bonding process including
the friction contact between tool and wire. This model yields novel insights into
the process. A prototype of a multi-objective optimizing bonding machine (MOBM)
is presented. It uses multi-objective optimization, based on the complete process
model, to automatically select the best operating point as a compromise of concurrent
objectives.
author:
- first_name: Andreas
full_name: Unger, Andreas
last_name: Unger
- first_name: Matthias
full_name: Hunstig, Matthias
last_name: Hunstig
- first_name: Tobias
full_name: Meyer, Tobias
last_name: Meyer
- first_name: Michael
full_name: Brökelmann, Michael
last_name: Brökelmann
- first_name: Walter
full_name: Sextro, Walter
id: '21220'
last_name: Sextro
citation:
ama: 'Unger A, Hunstig M, Meyer T, Brökelmann M, Sextro W. Intelligent Production
of Wire Bonds using Multi-Objective Optimization – Insights, Opportunities and
Challenges. In: In Proceedings of IMAPS 2018 – 51st Symposium on Microelectronics,
Pasadena, CA, 2018. Vol Vol. 2018, No. 1, pp. 000572-000577. ; 2018. doi:10.4071/2380-4505-2018.1.000572'
apa: Unger, A., Hunstig, M., Meyer, T., Brökelmann, M., & Sextro, W. (2018).
Intelligent Production of Wire Bonds using Multi-Objective Optimization – Insights,
Opportunities and Challenges. In In Proceedings of IMAPS 2018 – 51st Symposium
on Microelectronics, Pasadena, CA, 2018 (Vol. Vol. 2018, No. 1, pp. 000572-000577.).
https://doi.org/10.4071/2380-4505-2018.1.000572
bibtex: '@inproceedings{Unger_Hunstig_Meyer_Brökelmann_Sextro_2018, title={Intelligent
Production of Wire Bonds using Multi-Objective Optimization – Insights, Opportunities
and Challenges}, volume={Vol. 2018, No. 1, pp. 000572-000577.}, DOI={10.4071/2380-4505-2018.1.000572},
booktitle={In Proceedings of IMAPS 2018 – 51st Symposium on Microelectronics,
Pasadena, CA, 2018}, author={Unger, Andreas and Hunstig, Matthias and Meyer, Tobias
and Brökelmann, Michael and Sextro, Walter}, year={2018} }'
chicago: Unger, Andreas, Matthias Hunstig, Tobias Meyer, Michael Brökelmann, and
Walter Sextro. “Intelligent Production of Wire Bonds Using Multi-Objective Optimization
– Insights, Opportunities and Challenges.” In In Proceedings of IMAPS 2018
– 51st Symposium on Microelectronics, Pasadena, CA, 2018, Vol. Vol. 2018,
No. 1, pp. 000572-000577., 2018. https://doi.org/10.4071/2380-4505-2018.1.000572.
ieee: A. Unger, M. Hunstig, T. Meyer, M. Brökelmann, and W. Sextro, “Intelligent
Production of Wire Bonds using Multi-Objective Optimization – Insights, Opportunities
and Challenges,” in In Proceedings of IMAPS 2018 – 51st Symposium on Microelectronics,
Pasadena, CA, 2018, 2018, vol. Vol. 2018, No. 1, pp. 000572-000577.
mla: Unger, Andreas, et al. “Intelligent Production of Wire Bonds Using Multi-Objective
Optimization – Insights, Opportunities and Challenges.” In Proceedings of IMAPS
2018 – 51st Symposium on Microelectronics, Pasadena, CA, 2018, vol. Vol. 2018,
No. 1, pp. 000572-000577., 2018, doi:10.4071/2380-4505-2018.1.000572.
short: 'A. Unger, M. Hunstig, T. Meyer, M. Brökelmann, W. Sextro, in: In Proceedings
of IMAPS 2018 – 51st Symposium on Microelectronics, Pasadena, CA, 2018, 2018.'
date_created: 2019-05-27T10:27:45Z
date_updated: 2020-05-07T05:33:56Z
department:
- _id: '151'
doi: 10.4071/2380-4505-2018.1.000572
keyword:
- wire bonding
- multi-objective optimization
- process model
- copper wire
- self-optimization
language:
- iso: eng
project:
- _id: '92'
grant_number: 02 PQ2210
name: Intelligente Herstellung zuverlässiger Kupferbondverbindungen
publication: In Proceedings of IMAPS 2018 – 51st Symposium on Microelectronics, Pasadena,
CA, 2018
quality_controlled: '1'
status: public
title: Intelligent Production of Wire Bonds using Multi-Objective Optimization – Insights,
Opportunities and Challenges
type: conference
user_id: '210'
volume: Vol. 2018, No. 1, pp. 000572-000577.
year: '2018'
...
---
_id: '48839'
abstract:
- lang: eng
text: We analyze the effects of including local search techniques into a multi-objective
evolutionary algorithm for solving a bi-objective orienteering problem with a
single vehicle while the two conflicting objectives are minimization of travel
time and maximization of the number of visited customer locations. Experiments
are based on a large set of specifically designed problem instances with different
characteristics and it is shown that local search techniques focusing on one of
the objectives only improve the performance of the evolutionary algorithm in terms
of both objectives. The analysis also shows that local search techniques are capable
of sending locally optimal solutions to foremost fronts of the multi-objective
optimization process, and that these solutions then become the leading factors
of the evolutionary process.
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: Stephan
full_name: Meisel, Stephan
last_name: Meisel
- first_name: Günter
full_name: Rudolph, Günter
last_name: Rudolph
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Bossek J, Grimme C, Meisel S, Rudolph G, Trautmann H. Local Search Effects
in Bi-Objective Orienteering. In: Proceedings of the Genetic and Evolutionary
Computation Conference. GECCO ’18. Association for Computing Machinery; 2018:585–592.
doi:10.1145/3205455.3205548'
apa: Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2018).
Local Search Effects in Bi-Objective Orienteering. Proceedings of the Genetic
and Evolutionary Computation Conference, 585–592. https://doi.org/10.1145/3205455.3205548
bibtex: '@inproceedings{Bossek_Grimme_Meisel_Rudolph_Trautmann_2018, place={New
York, NY, USA}, series={GECCO ’18}, title={Local Search Effects in Bi-Objective
Orienteering}, DOI={10.1145/3205455.3205548},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
publisher={Association for Computing Machinery}, author={Bossek, Jakob and Grimme,
Christian and Meisel, Stephan and Rudolph, Günter and Trautmann, Heike}, year={2018},
pages={585–592}, collection={GECCO ’18} }'
chicago: 'Bossek, Jakob, Christian Grimme, Stephan Meisel, Günter Rudolph, and Heike
Trautmann. “Local Search Effects in Bi-Objective Orienteering.” In Proceedings
of the Genetic and Evolutionary Computation Conference, 585–592. GECCO ’18.
New York, NY, USA: Association for Computing Machinery, 2018. https://doi.org/10.1145/3205455.3205548.'
ieee: 'J. Bossek, C. Grimme, S. Meisel, G. Rudolph, and H. Trautmann, “Local Search
Effects in Bi-Objective Orienteering,” in Proceedings of the Genetic and Evolutionary
Computation Conference, 2018, pp. 585–592, doi: 10.1145/3205455.3205548.'
mla: Bossek, Jakob, et al. “Local Search Effects in Bi-Objective Orienteering.”
Proceedings of the Genetic and Evolutionary Computation Conference, Association
for Computing Machinery, 2018, pp. 585–592, doi:10.1145/3205455.3205548.
short: 'J. Bossek, C. Grimme, S. Meisel, G. Rudolph, H. Trautmann, in: Proceedings
of the Genetic and Evolutionary Computation Conference, Association for Computing
Machinery, New York, NY, USA, 2018, pp. 585–592.'
date_created: 2023-11-14T15:58:51Z
date_updated: 2023-12-13T10:42:14Z
department:
- _id: '819'
doi: 10.1145/3205455.3205548
extern: '1'
keyword:
- combinatorial optimization
- metaheuristics
- multi-objective optimization
- orienteering
- transportation
language:
- iso: eng
page: 585–592
place: New York, NY, USA
publication: Proceedings of the Genetic and Evolutionary Computation Conference
publication_identifier:
isbn:
- 978-1-4503-5618-3
publication_status: published
publisher: Association for Computing Machinery
series_title: GECCO ’18
status: public
title: Local Search Effects in Bi-Objective Orienteering
type: conference
user_id: '102979'
year: '2018'
...
---
_id: '29973'
abstract:
- lang: eng
text: 'Haushaltsgeräte aus der Klasse der "Weißen Ware" tragen mit etwa einem Drittel
($34,2%$ \citeBDEW2013) zum privaten Energieverbrauch bei. Diese Veröffentlichung
präsentiert eine Struktur und die dafür notwendige optimale Betriebsstrategie
für Weiße Ware in einer Umgebung mit Strompreisen, die wegen der Volatilität der
Regenerativen Energien stark fluktuieren. Das vorgeschlagene Konzept nutzt dafür
ein dezentrales Energiemanagementsystem, das über drei Hierarchieebenen verteilt
ist: die Geräteebene, die Haushaltsebene und die Ortsnetzebene. Auf der Geräteebene
nutzt dieses Konzept zusätzlich Betriebsflexibilitäten der Haushaltsgeräte aus.'
author:
- first_name: Karl Stephan Christian
full_name: Stille, Karl Stephan Christian
id: '30152'
last_name: Stille
orcid: 0000-0002-4212-6555
- first_name: Joachim
full_name: Böcker, Joachim
id: '66'
last_name: Böcker
orcid: 0000-0002-8480-7295
- first_name: Ralf
full_name: Bettentrup, Ralf
last_name: Bettentrup
- first_name: Ingo
full_name: Kaiser, Ingo
last_name: Kaiser
citation:
ama: 'Stille KSC, Böcker J, Bettentrup R, Kaiser I. Hierarchisches Optimierungskonzept
für die Laststeuerung von Haushaltsgeräten. In: ETG-Fachtagung “Von Smart Grids
Zu Smart Markets.” VDE; 2015.'
apa: Stille, K. S. C., Böcker, J., Bettentrup, R., & Kaiser, I. (2015). Hierarchisches
Optimierungskonzept für die Laststeuerung von Haushaltsgeräten. ETG-Fachtagung
“Von Smart Grids Zu Smart Markets.”
bibtex: '@inproceedings{Stille_Böcker_Bettentrup_Kaiser_2015, place={Kassel}, title={Hierarchisches
Optimierungskonzept für die Laststeuerung von Haushaltsgeräten}, booktitle={ETG-Fachtagung
“Von Smart Grids zu Smart Markets”}, publisher={VDE}, author={Stille, Karl Stephan
Christian and Böcker, Joachim and Bettentrup, Ralf and Kaiser, Ingo}, year={2015}
}'
chicago: 'Stille, Karl Stephan Christian, Joachim Böcker, Ralf Bettentrup, and Ingo
Kaiser. “Hierarchisches Optimierungskonzept Für Die Laststeuerung von Haushaltsgeräten.”
In ETG-Fachtagung “Von Smart Grids Zu Smart Markets.” Kassel: VDE, 2015.'
ieee: K. S. C. Stille, J. Böcker, R. Bettentrup, and I. Kaiser, “Hierarchisches
Optimierungskonzept für die Laststeuerung von Haushaltsgeräten,” 2015.
mla: Stille, Karl Stephan Christian, et al. “Hierarchisches Optimierungskonzept
Für Die Laststeuerung von Haushaltsgeräten.” ETG-Fachtagung “Von Smart Grids
Zu Smart Markets,” VDE, 2015.
short: 'K.S.C. Stille, J. Böcker, R. Bettentrup, I. Kaiser, in: ETG-Fachtagung “Von
Smart Grids Zu Smart Markets,” VDE, Kassel, 2015.'
date_created: 2022-02-23T09:24:36Z
date_updated: 2022-02-23T16:10:58Z
department:
- _id: '52'
keyword:
- Energy management
- hybrid energy storage system
- self-optimization
- multi-objective optimization
- adaptive systems
- pareto set
- SFB614-D1
- SFB614-D2
- LEA-Publikation
- Eigene
language:
- iso: eng
main_file_link:
- url: https://www.vde-verlag.de/proceedings-en/453897045.html
place: Kassel
publication: ETG-Fachtagung "Von Smart Grids zu Smart Markets"
publisher: VDE
status: public
title: Hierarchisches Optimierungskonzept für die Laststeuerung von Haushaltsgeräten
type: conference
user_id: '66'
year: '2015'
...
---
_id: '48887'
abstract:
- lang: eng
text: 'We evaluate the performance of a multi-objective evolutionary algorithm on
a class of dynamic routing problems with a single vehicle. In particular we focus
on relating algorithmic performance to the most prominent characteristics of problem
instances. The routing problem considers two types of customers: mandatory customers
must be visited whereas optional customers do not necessarily have to be visited.
Moreover, mandatory customers are known prior to the start of the tour whereas
optional customers request for service at later points in time with the vehicle
already being on its way. The multi-objective optimization problem then results
as maximizing the number of visited customers while simultaneously minimizing
total travel time. As an a-posteriori evaluation tool, the evolutionary algorithm
aims at approximating the related Pareto set for specifically designed benchmarking
instances differing in terms of number of customers, geographical layout, fraction
of mandatory customers, and request times of optional customers. Conceptional
and experimental comparisons to online heuristic procedures are provided.'
author:
- first_name: Stephan
full_name: Meisel, Stephan
last_name: Meisel
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Martin
full_name: Wölck, Martin
last_name: Wölck
- first_name: Günter
full_name: Rudolph, Günter
last_name: Rudolph
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
citation:
ama: 'Meisel S, Grimme C, Bossek J, Wölck M, Rudolph G, Trautmann H. Evaluation
of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle.
In: Proceedings of the Genetic and Evolutionary Computation Conference .
GECCO’15. Association for Computing Machinery; 2015:425–432. doi:10.1145/2739480.2754705'
apa: Meisel, S., Grimme, C., Bossek, J., Wölck, M., Rudolph, G., & Trautmann,
H. (2015). Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic
Routing of a Vehicle. Proceedings of the Genetic and Evolutionary Computation
Conference , 425–432. https://doi.org/10.1145/2739480.2754705
bibtex: '@inproceedings{Meisel_Grimme_Bossek_Wölck_Rudolph_Trautmann_2015, place={New
York, NY, USA}, series={GECCO’15}, title={Evaluation of a Multi-Objective EA on
Benchmark Instances for Dynamic Routing of a Vehicle}, DOI={10.1145/2739480.2754705},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference
}, publisher={Association for Computing Machinery}, author={Meisel, Stephan and
Grimme, Christian and Bossek, Jakob and Wölck, Martin and Rudolph, Günter and
Trautmann, Heike}, year={2015}, pages={425–432}, collection={GECCO’15} }'
chicago: 'Meisel, Stephan, Christian Grimme, Jakob Bossek, Martin Wölck, Günter
Rudolph, and Heike Trautmann. “Evaluation of a Multi-Objective EA on Benchmark
Instances for Dynamic Routing of a Vehicle.” In Proceedings of the Genetic
and Evolutionary Computation Conference , 425–432. GECCO’15. New York, NY,
USA: Association for Computing Machinery, 2015. https://doi.org/10.1145/2739480.2754705.'
ieee: 'S. Meisel, C. Grimme, J. Bossek, M. Wölck, G. Rudolph, and H. Trautmann,
“Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing
of a Vehicle,” in Proceedings of the Genetic and Evolutionary Computation Conference
, 2015, pp. 425–432, doi: 10.1145/2739480.2754705.'
mla: Meisel, Stephan, et al. “Evaluation of a Multi-Objective EA on Benchmark Instances
for Dynamic Routing of a Vehicle.” Proceedings of the Genetic and Evolutionary
Computation Conference , Association for Computing Machinery, 2015, pp. 425–432,
doi:10.1145/2739480.2754705.
short: 'S. Meisel, C. Grimme, J. Bossek, M. Wölck, G. Rudolph, H. Trautmann, in:
Proceedings of the Genetic and Evolutionary Computation Conference , Association
for Computing Machinery, New York, NY, USA, 2015, pp. 425–432.'
date_created: 2023-11-14T15:58:59Z
date_updated: 2023-12-13T10:49:06Z
department:
- _id: '819'
doi: 10.1145/2739480.2754705
extern: '1'
keyword:
- combinatorial optimization
- metaheuristics
- multi-objective optimization
- online algorithms
- transportation
language:
- iso: eng
page: 425–432
place: New York, NY, USA
publication: 'Proceedings of the Genetic and Evolutionary Computation Conference '
publication_identifier:
isbn:
- 978-1-4503-3472-3
publisher: Association for Computing Machinery
series_title: GECCO’15
status: public
title: Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing
of a Vehicle
type: conference
user_id: '102979'
year: '2015'
...