---
_id: '52759'
author:
- first_name: Oliver Ludger
full_name: Preuß, Oliver Ludger
id: '102978'
last_name: Preuß
orcid: 0009-0008-9308-2418
- first_name: Jeroen
full_name: Rook, Jeroen
last_name: Rook
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Preuß OL, Rook J, Trautmann H. On the Potential of Multi-objective Automated
Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems.
In: Applications of Evolutionary Computation. Springer Nature Switzerland;
2024. doi:10.1007/978-3-031-56852-7_20'
apa: Preuß, O. L., Rook, J., & Trautmann, H. (2024). On the Potential of Multi-objective
Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation
Problems. In Applications of Evolutionary Computation. Springer Nature
Switzerland. https://doi.org/10.1007/978-3-031-56852-7_20
bibtex: '@inbook{Preuß_Rook_Trautmann_2024, place={Cham}, title={On the Potential
of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective
Optimisation Problems}, DOI={10.1007/978-3-031-56852-7_20},
booktitle={Applications of Evolutionary Computation}, publisher={Springer Nature
Switzerland}, author={Preuß, Oliver Ludger and Rook, Jeroen and Trautmann, Heike},
year={2024} }'
chicago: 'Preuß, Oliver Ludger, Jeroen Rook, and Heike Trautmann. “On the Potential
of Multi-Objective Automated Algorithm Configuration on Multi-Modal Multi-Objective
Optimisation Problems.” In Applications of Evolutionary Computation. Cham:
Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-56852-7_20.'
ieee: 'O. L. Preuß, J. Rook, and H. Trautmann, “On the Potential of Multi-objective
Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation
Problems,” in Applications of Evolutionary Computation, Cham: Springer
Nature Switzerland, 2024.'
mla: Preuß, Oliver Ludger, et al. “On the Potential of Multi-Objective Automated
Algorithm Configuration on Multi-Modal Multi-Objective Optimisation Problems.”
Applications of Evolutionary Computation, Springer Nature Switzerland,
2024, doi:10.1007/978-3-031-56852-7_20.
short: 'O.L. Preuß, J. Rook, H. Trautmann, in: Applications of Evolutionary Computation,
Springer Nature Switzerland, Cham, 2024.'
date_created: 2024-03-25T08:22:57Z
date_updated: 2024-06-10T11:55:38Z
department:
- _id: '819'
doi: 10.1007/978-3-031-56852-7_20
language:
- iso: eng
place: Cham
publication: Applications of Evolutionary Computation
publication_identifier:
isbn:
- '9783031568510'
- '9783031568527'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal
Multi-objective Optimisation Problems
type: book_chapter
user_id: '15504'
year: '2024'
...
---
_id: '52749'
author:
- first_name: Moritz
full_name: Seiler, Moritz
id: '105520'
last_name: Seiler
- first_name: Jeroen
full_name: Rook, Jeroen
last_name: Rook
- first_name: Jonathan
full_name: Heins, Jonathan
last_name: Heins
- first_name: Oliver Ludger
full_name: Preuß, Oliver Ludger
id: '102978'
last_name: Preuß
orcid: 0009-0008-9308-2418
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Seiler M, Rook J, Heins J, Preuß OL, Bossek J, Trautmann H. Using Reinforcement
Learning for Per-Instance Algorithm Configuration on the TSP. In: 2023 IEEE
Symposium Series on Computational Intelligence (SSCI). IEEE; 2024. doi:10.1109/ssci52147.2023.10372008'
apa: Seiler, M., Rook, J., Heins, J., Preuß, O. L., Bossek, J., & Trautmann,
H. (2024). Using Reinforcement Learning for Per-Instance Algorithm Configuration
on the TSP. 2023 IEEE Symposium Series on Computational Intelligence (SSCI).
https://doi.org/10.1109/ssci52147.2023.10372008
bibtex: '@inproceedings{Seiler_Rook_Heins_Preuß_Bossek_Trautmann_2024, title={Using
Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP}, DOI={10.1109/ssci52147.2023.10372008},
booktitle={2023 IEEE Symposium Series on Computational Intelligence (SSCI)}, publisher={IEEE},
author={Seiler, Moritz and Rook, Jeroen and Heins, Jonathan and Preuß, Oliver
Ludger and Bossek, Jakob and Trautmann, Heike}, year={2024} }'
chicago: Seiler, Moritz, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob
Bossek, and Heike Trautmann. “Using Reinforcement Learning for Per-Instance Algorithm
Configuration on the TSP.” In 2023 IEEE Symposium Series on Computational Intelligence
(SSCI). IEEE, 2024. https://doi.org/10.1109/ssci52147.2023.10372008.
ieee: 'M. Seiler, J. Rook, J. Heins, O. L. Preuß, J. Bossek, and H. Trautmann, “Using
Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP,” 2024,
doi: 10.1109/ssci52147.2023.10372008.'
mla: Seiler, Moritz, et al. “Using Reinforcement Learning for Per-Instance Algorithm
Configuration on the TSP.” 2023 IEEE Symposium Series on Computational Intelligence
(SSCI), IEEE, 2024, doi:10.1109/ssci52147.2023.10372008.
short: 'M. Seiler, J. Rook, J. Heins, O.L. Preuß, J. Bossek, H. Trautmann, in: 2023
IEEE Symposium Series on Computational Intelligence (SSCI), IEEE, 2024.'
date_created: 2024-03-25T08:15:01Z
date_updated: 2024-06-10T11:59:44Z
department:
- _id: '819'
doi: 10.1109/ssci52147.2023.10372008
language:
- iso: eng
publication: 2023 IEEE Symposium Series on Computational Intelligence (SSCI)
publication_status: published
publisher: IEEE
status: public
title: Using Reinforcement Learning for Per-Instance Algorithm Configuration on the
TSP
type: conference
user_id: '15504'
year: '2024'
...
---
_id: '55649'
author:
- first_name: Jeroen
full_name: Rook, Jeroen
last_name: Rook
- first_name: Holger H.
full_name: Hoos, Holger H.
last_name: Hoos
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Rook J, Hoos HH, Trautmann H. Multi-objective Ranking using Bootstrap Resampling.
In: Li X, Handl J, eds. Proceedings of the Genetic and Evolutionary Computation
Conference Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024.
ACM; 2024:155–158. doi:10.1145/3638530.3654436'
apa: Rook, J., Hoos, H. H., & Trautmann, H. (2024). Multi-objective Ranking
using Bootstrap Resampling. In X. Li & J. Handl (Eds.), Proceedings of
the Genetic and Evolutionary Computation Conference Companion, GECCO 2024, Melbourne,
VIC, Australia, July 14-18, 2024 (pp. 155–158). ACM. https://doi.org/10.1145/3638530.3654436
bibtex: '@inproceedings{Rook_Hoos_Trautmann_2024, title={Multi-objective Ranking
using Bootstrap Resampling}, DOI={10.1145/3638530.3654436},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference
Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024}, publisher={ACM},
author={Rook, Jeroen and Hoos, Holger H. and Trautmann, Heike}, editor={Li, Xiaodong
and Handl, Julia}, year={2024}, pages={155–158} }'
chicago: Rook, Jeroen, Holger H. Hoos, and Heike Trautmann. “Multi-Objective Ranking
Using Bootstrap Resampling.” In Proceedings of the Genetic and Evolutionary
Computation Conference Companion, GECCO 2024, Melbourne, VIC, Australia, July
14-18, 2024, edited by Xiaodong Li and Julia Handl, 155–158. ACM, 2024. https://doi.org/10.1145/3638530.3654436.
ieee: 'J. Rook, H. H. Hoos, and H. Trautmann, “Multi-objective Ranking using Bootstrap
Resampling,” in Proceedings of the Genetic and Evolutionary Computation Conference
Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024, 2024,
pp. 155–158, doi: 10.1145/3638530.3654436.'
mla: Rook, Jeroen, et al. “Multi-Objective Ranking Using Bootstrap Resampling.”
Proceedings of the Genetic and Evolutionary Computation Conference Companion,
GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024, edited by Xiaodong
Li and Julia Handl, ACM, 2024, pp. 155–158, doi:10.1145/3638530.3654436.
short: 'J. Rook, H.H. Hoos, H. Trautmann, in: X. Li, J. Handl (Eds.), Proceedings
of the Genetic and Evolutionary Computation Conference Companion, GECCO 2024,
Melbourne, VIC, Australia, July 14-18, 2024, ACM, 2024, pp. 155–158.'
date_created: 2024-08-19T09:34:07Z
date_updated: 2024-08-19T09:34:45Z
doi: 10.1145/3638530.3654436
editor:
- first_name: Xiaodong
full_name: Li, Xiaodong
last_name: Li
- first_name: Julia
full_name: Handl, Julia
last_name: Handl
language:
- iso: eng
page: 155–158
publication: Proceedings of the Genetic and Evolutionary Computation Conference Companion,
GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024
publisher: ACM
status: public
title: Multi-objective Ranking using Bootstrap Resampling
type: conference
user_id: '15504'
year: '2024'
...
---
_id: '56221'
author:
- first_name: Angel E.
full_name: Rodriguez-Fernandez, Angel E.
last_name: Rodriguez-Fernandez
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Carlos
full_name: Hernández, Carlos
last_name: Hernández
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Oliver
full_name: Schütze, Oliver
last_name: Schütze
citation:
ama: Rodriguez-Fernandez AE, Schäpermeier L, Hernández C, Kerschke P, Trautmann
H, Schütze O. Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal
Optimization. IEEE Transactions on Evolutionary Computation. Published
online 2024:1-1. doi:10.1109/TEVC.2024.3458855
apa: Rodriguez-Fernandez, A. E., Schäpermeier, L., Hernández, C., Kerschke, P.,
Trautmann, H., & Schütze, O. (2024). Finding ϵ-Locally Optimal Solutions for
Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary
Computation, 1–1. https://doi.org/10.1109/TEVC.2024.3458855
bibtex: '@article{Rodriguez-Fernandez_Schäpermeier_Hernández_Kerschke_Trautmann_Schütze_2024,
title={Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization},
DOI={10.1109/TEVC.2024.3458855},
journal={IEEE Transactions on Evolutionary Computation}, author={Rodriguez-Fernandez,
Angel E. and Schäpermeier, Lennart and Hernández, Carlos and Kerschke, Pascal
and Trautmann, Heike and Schütze, Oliver}, year={2024}, pages={1–1} }'
chicago: Rodriguez-Fernandez, Angel E., Lennart Schäpermeier, Carlos Hernández,
Pascal Kerschke, Heike Trautmann, and Oliver Schütze. “Finding ϵ-Locally Optimal
Solutions for Multi-Objective Multimodal Optimization.” IEEE Transactions on
Evolutionary Computation, 2024, 1–1. https://doi.org/10.1109/TEVC.2024.3458855.
ieee: 'A. E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H.
Trautmann, and O. Schütze, “Finding ϵ-Locally Optimal Solutions for Multi-Objective
Multimodal Optimization,” IEEE Transactions on Evolutionary Computation,
pp. 1–1, 2024, doi: 10.1109/TEVC.2024.3458855.'
mla: Rodriguez-Fernandez, Angel E., et al. “Finding ϵ-Locally Optimal Solutions
for Multi-Objective Multimodal Optimization.” IEEE Transactions on Evolutionary
Computation, 2024, pp. 1–1, doi:10.1109/TEVC.2024.3458855.
short: A.E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H.
Trautmann, O. Schütze, IEEE Transactions on Evolutionary Computation (2024) 1–1.
date_created: 2024-09-24T08:01:14Z
date_updated: 2024-09-24T08:01:47Z
doi: 10.1109/TEVC.2024.3458855
keyword:
- Optimization
- Evolutionary computation
- Approximation algorithms
- Benchmark testing
- Vectors
- Surveys
- Pareto optimization
- multi-objective optimization
- evolutionary computation
- multimodal optimization
- local solutions
language:
- iso: eng
page: 1-1
publication: IEEE Transactions on Evolutionary Computation
status: public
title: Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization
type: journal_article
user_id: '15504'
year: '2024'
...
---
_id: '58335'
author:
- first_name: Moritz
full_name: Seiler, Moritz
id: '105520'
last_name: Seiler
- first_name: Urban
full_name: Skvorc, Urban
id: '103764'
last_name: Skvorc
- first_name: Carola
full_name: Doerr, Carola
last_name: Doerr
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Seiler M, Skvorc U, Doerr C, Trautmann H. Synergies of Deep and Classical
Exploratory Landscape Features for Automated Algorithm Selection. In: Festa P,
Ferone D, Pastore T, Pisacane O, eds. Learning and Intelligent Optimization
- 18th International Conference, LION 18, Ischia Island, Italy, June 9-13, 2024,
Revised Selected Papers. Vol 14990. Lecture Notes in Computer Science. Springer;
2024:361–376. doi:10.1007/978-3-031-75623-8_29'
apa: Seiler, M., Skvorc, U., Doerr, C., & Trautmann, H. (2024). Synergies of
Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection.
In P. Festa, D. Ferone, T. Pastore, & O. Pisacane (Eds.), Learning and
Intelligent Optimization - 18th International Conference, LION 18, Ischia Island,
Italy, June 9-13, 2024, Revised Selected Papers (Vol. 14990, pp. 361–376).
Springer. https://doi.org/10.1007/978-3-031-75623-8_29
bibtex: '@inproceedings{Seiler_Skvorc_Doerr_Trautmann_2024, series={Lecture Notes
in Computer Science}, title={Synergies of Deep and Classical Exploratory Landscape
Features for Automated Algorithm Selection}, volume={14990}, DOI={10.1007/978-3-031-75623-8_29},
booktitle={Learning and Intelligent Optimization - 18th International Conference,
LION 18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers}, publisher={Springer},
author={Seiler, Moritz and Skvorc, Urban and Doerr, Carola and Trautmann, Heike},
editor={Festa, Paola and Ferone, Daniele and Pastore, Tommaso and Pisacane, Ornella},
year={2024}, pages={361–376}, collection={Lecture Notes in Computer Science} }'
chicago: Seiler, Moritz, Urban Skvorc, Carola Doerr, and Heike Trautmann. “Synergies
of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection.”
In Learning and Intelligent Optimization - 18th International Conference, LION
18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers, edited
by Paola Festa, Daniele Ferone, Tommaso Pastore, and Ornella Pisacane, 14990:361–376.
Lecture Notes in Computer Science. Springer, 2024. https://doi.org/10.1007/978-3-031-75623-8_29.
ieee: 'M. Seiler, U. Skvorc, C. Doerr, and H. Trautmann, “Synergies of Deep and
Classical Exploratory Landscape Features for Automated Algorithm Selection,” in
Learning and Intelligent Optimization - 18th International Conference, LION
18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers, 2024,
vol. 14990, pp. 361–376, doi: 10.1007/978-3-031-75623-8_29.'
mla: Seiler, Moritz, et al. “Synergies of Deep and Classical Exploratory Landscape
Features for Automated Algorithm Selection.” Learning and Intelligent Optimization
- 18th International Conference, LION 18, Ischia Island, Italy, June 9-13, 2024,
Revised Selected Papers, edited by Paola Festa et al., vol. 14990, Springer,
2024, pp. 361–376, doi:10.1007/978-3-031-75623-8_29.
short: 'M. Seiler, U. Skvorc, C. Doerr, H. Trautmann, in: P. Festa, D. Ferone, T.
Pastore, O. Pisacane (Eds.), Learning and Intelligent Optimization - 18th International
Conference, LION 18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers,
Springer, 2024, pp. 361–376.'
date_created: 2025-01-23T12:39:37Z
date_updated: 2025-01-23T12:40:32Z
department:
- _id: '819'
doi: 10.1007/978-3-031-75623-8_29
editor:
- first_name: Paola
full_name: Festa, Paola
last_name: Festa
- first_name: Daniele
full_name: Ferone, Daniele
last_name: Ferone
- first_name: Tommaso
full_name: Pastore, Tommaso
last_name: Pastore
- first_name: Ornella
full_name: Pisacane, Ornella
last_name: Pisacane
intvolume: ' 14990'
language:
- iso: eng
page: 361–376
publication: Learning and Intelligent Optimization - 18th International Conference,
LION 18, Ischia Island, Italy, June 9-13, 2024, Revised Selected Papers
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Synergies of Deep and Classical Exploratory Landscape Features for Automated
Algorithm Selection
type: conference
user_id: '15504'
volume: 14990
year: '2024'
...
---
_id: '58338'
citation:
ama: Affenzeller M, Winkler SM, Kononova AV, et al., eds. Parallel Problem Solving
from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg,
Austria, September 14-18, 2024, Proceedings, Part III. Vol 15150. Springer;
2024. doi:10.1007/978-3-031-70071-2
apa: Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T.,
Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part III (Vol. 15150). Springer. https://doi.org/10.1007/978-3-031-70071-2
bibtex: '@book{Affenzeller_Winkler_Kononova_Trautmann_Tusar_Machado_Bäck_2024, series={Lecture
Notes in Computer Science}, title={Parallel Problem Solving from Nature - PPSN
XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part III}, volume={15150}, DOI={10.1007/978-3-031-70071-2},
publisher={Springer}, year={2024}, collection={Lecture Notes in Computer Science}
}'
chicago: Affenzeller, Michael, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann,
Tea Tusar, Penousal Machado, and Thomas Bäck, eds. Parallel Problem Solving
from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg,
Austria, September 14-18, 2024, Proceedings, Part III. Vol. 15150. Lecture
Notes in Computer Science. Springer, 2024. https://doi.org/10.1007/978-3-031-70071-2.
ieee: M. Affenzeller et al., Eds., Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part III, vol. 15150. Springer, 2024.
mla: Affenzeller, Michael, et al., editors. Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part III. Springer, 2024, doi:10.1007/978-3-031-70071-2.
short: M. Affenzeller, S.M. Winkler, A.V. Kononova, H. Trautmann, T. Tusar, P. Machado,
T. Bäck, eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International
Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings,
Part III, Springer, 2024.
date_created: 2025-01-23T12:42:54Z
date_updated: 2025-01-23T12:44:21Z
department:
- _id: '819'
doi: 10.1007/978-3-031-70071-2
editor:
- first_name: Michael
full_name: Affenzeller, Michael
last_name: Affenzeller
- first_name: Stephan M.
full_name: Winkler, Stephan M.
last_name: Winkler
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Tea
full_name: Tusar, Tea
last_name: Tusar
- first_name: Penousal
full_name: Machado, Penousal
last_name: Machado
- first_name: Thomas
full_name: Bäck, Thomas
last_name: Bäck
intvolume: ' 15150'
language:
- iso: eng
publication_identifier:
isbn:
- 978-3-031-70070-5
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference,
PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part III
type: conference_editor
user_id: '15504'
volume: 15150
year: '2024'
...
---
_id: '58336'
citation:
ama: Affenzeller M, Winkler SM, Kononova AV, et al., eds. Parallel Problem Solving
from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg,
Austria, September 14-18, 2024, Proceedings, Part I. Vol 15148. Springer;
2024. doi:10.1007/978-3-031-70055-2
apa: Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T.,
Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part I (Vol. 15148). Springer. https://doi.org/10.1007/978-3-031-70055-2
bibtex: '@book{Affenzeller_Winkler_Kononova_Trautmann_Tusar_Machado_Bäck_2024, series={Lecture
Notes in Computer Science}, title={Parallel Problem Solving from Nature - PPSN
XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part I}, volume={15148}, DOI={10.1007/978-3-031-70055-2},
publisher={Springer}, year={2024}, collection={Lecture Notes in Computer Science}
}'
chicago: Affenzeller, Michael, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann,
Tea Tusar, Penousal Machado, and Thomas Bäck, eds. Parallel Problem Solving
from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg,
Austria, September 14-18, 2024, Proceedings, Part I. Vol. 15148. Lecture Notes
in Computer Science. Springer, 2024. https://doi.org/10.1007/978-3-031-70055-2.
ieee: M. Affenzeller et al., Eds., Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part I, vol. 15148. Springer, 2024.
mla: Affenzeller, Michael, et al., editors. Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part I. Springer, 2024, doi:10.1007/978-3-031-70055-2.
short: M. Affenzeller, S.M. Winkler, A.V. Kononova, H. Trautmann, T. Tusar, P. Machado,
T. Bäck, eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International
Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings,
Part I, Springer, 2024.
date_created: 2025-01-23T12:41:21Z
date_updated: 2025-01-23T12:44:14Z
department:
- _id: '819'
doi: 10.1007/978-3-031-70055-2
editor:
- first_name: Michael
full_name: Affenzeller, Michael
last_name: Affenzeller
- first_name: Stephan M.
full_name: Winkler, Stephan M.
last_name: Winkler
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Tea
full_name: Tusar, Tea
last_name: Tusar
- first_name: Penousal
full_name: Machado, Penousal
last_name: Machado
- first_name: Thomas
full_name: Bäck, Thomas
last_name: Bäck
intvolume: ' 15148'
language:
- iso: eng
publication_identifier:
isbn:
- 978-3-031-70054-5
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference,
PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part I
type: conference_editor
user_id: '15504'
volume: 15148
year: '2024'
...
---
_id: '58339'
citation:
ama: Affenzeller M, Winkler SM, Kononova AV, et al., eds. Parallel Problem Solving
from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg,
Austria, September 14-18, 2024, Proceedings, Part IV. Vol 15151. Springer;
2024. doi:10.1007/978-3-031-70085-9
apa: Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T.,
Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part IV (Vol. 15151). Springer. https://doi.org/10.1007/978-3-031-70085-9
bibtex: '@book{Affenzeller_Winkler_Kononova_Trautmann_Tusar_Machado_Bäck_2024, series={Lecture
Notes in Computer Science}, title={Parallel Problem Solving from Nature - PPSN
XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part IV}, volume={15151}, DOI={10.1007/978-3-031-70085-9},
publisher={Springer}, year={2024}, collection={Lecture Notes in Computer Science}
}'
chicago: Affenzeller, Michael, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann,
Tea Tusar, Penousal Machado, and Thomas Bäck, eds. Parallel Problem Solving
from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg,
Austria, September 14-18, 2024, Proceedings, Part IV. Vol. 15151. Lecture
Notes in Computer Science. Springer, 2024. https://doi.org/10.1007/978-3-031-70085-9.
ieee: M. Affenzeller et al., Eds., Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part IV, vol. 15151. Springer, 2024.
mla: Affenzeller, Michael, et al., editors. Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part IV. Springer, 2024, doi:10.1007/978-3-031-70085-9.
short: M. Affenzeller, S.M. Winkler, A.V. Kononova, H. Trautmann, T. Tusar, P. Machado,
T. Bäck, eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International
Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings,
Part IV, Springer, 2024.
date_created: 2025-01-23T12:43:27Z
date_updated: 2025-01-23T12:44:17Z
department:
- _id: '819'
doi: 10.1007/978-3-031-70085-9
editor:
- first_name: Michael
full_name: Affenzeller, Michael
last_name: Affenzeller
- first_name: Stephan M.
full_name: Winkler, Stephan M.
last_name: Winkler
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Tea
full_name: Tusar, Tea
last_name: Tusar
- first_name: Penousal
full_name: Machado, Penousal
last_name: Machado
- first_name: Thomas
full_name: Bäck, Thomas
last_name: Bäck
intvolume: ' 15151'
language:
- iso: eng
publication_identifier:
isbn:
- 978-3-031-70084-2
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference,
PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part IV
type: conference_editor
user_id: '15504'
volume: 15151
year: '2024'
...
---
_id: '58337'
citation:
ama: Affenzeller M, Winkler SM, Kononova AV, et al., eds. Parallel Problem Solving
from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg,
Austria, September 14-18, 2024, Proceedings, Part II. Vol 15149. Springer;
2024. doi:10.1007/978-3-031-70068-2
apa: Affenzeller, M., Winkler, S. M., Kononova, A. V., Trautmann, H., Tusar, T.,
Machado, P., & Bäck, T. (Eds.). (2024). Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part II (Vol. 15149). Springer. https://doi.org/10.1007/978-3-031-70068-2
bibtex: '@book{Affenzeller_Winkler_Kononova_Trautmann_Tusar_Machado_Bäck_2024, series={Lecture
Notes in Computer Science}, title={Parallel Problem Solving from Nature - PPSN
XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part II}, volume={15149}, DOI={10.1007/978-3-031-70068-2},
publisher={Springer}, year={2024}, collection={Lecture Notes in Computer Science}
}'
chicago: Affenzeller, Michael, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann,
Tea Tusar, Penousal Machado, and Thomas Bäck, eds. Parallel Problem Solving
from Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg,
Austria, September 14-18, 2024, Proceedings, Part II. Vol. 15149. Lecture
Notes in Computer Science. Springer, 2024. https://doi.org/10.1007/978-3-031-70068-2.
ieee: M. Affenzeller et al., Eds., Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part II, vol. 15149. Springer, 2024.
mla: Affenzeller, Michael, et al., editors. Parallel Problem Solving from Nature
- PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria, September
14-18, 2024, Proceedings, Part II. Springer, 2024, doi:10.1007/978-3-031-70068-2.
short: M. Affenzeller, S.M. Winkler, A.V. Kononova, H. Trautmann, T. Tusar, P. Machado,
T. Bäck, eds., Parallel Problem Solving from Nature - PPSN XVIII - 18th International
Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings,
Part II, Springer, 2024.
date_created: 2025-01-23T12:42:15Z
date_updated: 2025-01-23T12:44:24Z
doi: 10.1007/978-3-031-70068-2
editor:
- first_name: Michael
full_name: Affenzeller, Michael
last_name: Affenzeller
- first_name: Stephan M.
full_name: Winkler, Stephan M.
last_name: Winkler
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Tea
full_name: Tusar, Tea
last_name: Tusar
- first_name: Penousal
full_name: Machado, Penousal
last_name: Machado
- first_name: Thomas
full_name: Bäck, Thomas
last_name: Bäck
intvolume: ' 15149'
language:
- iso: eng
publication_identifier:
isbn:
- 978-3-031-70067-5
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference,
PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part II
type: conference_editor
user_id: '15504'
volume: 15149
year: '2024'
...
---
_id: '60131'
author:
- first_name: Oliver Ludger
full_name: Preuß, Oliver Ludger
id: '102978'
last_name: Preuß
orcid: 0009-0008-9308-2418
- first_name: Jeroen
full_name: Rook, Jeroen
id: '102977'
last_name: Rook
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Preuß OL, Rook J, Trautmann H. On the Potential of Multi-objective Automated
Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems.
In: Smith SL, Correia J, Cintrano C, eds. Applications of Evolutionary Computation
- 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024,
Aberystwyth, UK, April 3-5, 2024, Proceedings, Part I. Vol 14634. Lecture
Notes in Computer Science. Springer; 2024:305–321. doi:10.1007/978-3-031-56852-7_20'
apa: Preuß, O. L., Rook, J., & Trautmann, H. (2024). On the Potential of Multi-objective
Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation
Problems. In S. L. Smith, J. Correia, & C. Cintrano (Eds.), Applications
of Evolutionary Computation - 27th European Conference, EvoApplications 2024,
Held as Part of EvoStar 2024, Aberystwyth, UK, April 3-5, 2024, Proceedings, Part
I (Vol. 14634, pp. 305–321). Springer. https://doi.org/10.1007/978-3-031-56852-7_20
bibtex: '@inproceedings{Preuß_Rook_Trautmann_2024, series={Lecture Notes in Computer
Science}, title={On the Potential of Multi-objective Automated Algorithm Configuration
on Multi-modal Multi-objective Optimisation Problems}, volume={14634}, DOI={10.1007/978-3-031-56852-7_20},
booktitle={Applications of Evolutionary Computation - 27th European Conference,
EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3-5,
2024, Proceedings, Part I}, publisher={Springer}, author={Preuß, Oliver Ludger
and Rook, Jeroen and Trautmann, Heike}, editor={Smith, Stephen L. and Correia,
João and Cintrano, Christian}, year={2024}, pages={305–321}, collection={Lecture
Notes in Computer Science} }'
chicago: Preuß, Oliver Ludger, Jeroen Rook, and Heike Trautmann. “On the Potential
of Multi-Objective Automated Algorithm Configuration on Multi-Modal Multi-Objective
Optimisation Problems.” In Applications of Evolutionary Computation - 27th
European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth,
UK, April 3-5, 2024, Proceedings, Part I, edited by Stephen L. Smith, João
Correia, and Christian Cintrano, 14634:305–321. Lecture Notes in Computer Science.
Springer, 2024. https://doi.org/10.1007/978-3-031-56852-7_20.
ieee: 'O. L. Preuß, J. Rook, and H. Trautmann, “On the Potential of Multi-objective
Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation
Problems,” in Applications of Evolutionary Computation - 27th European Conference,
EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3-5,
2024, Proceedings, Part I, 2024, vol. 14634, pp. 305–321, doi: 10.1007/978-3-031-56852-7_20.'
mla: Preuß, Oliver Ludger, et al. “On the Potential of Multi-Objective Automated
Algorithm Configuration on Multi-Modal Multi-Objective Optimisation Problems.”
Applications of Evolutionary Computation - 27th European Conference, EvoApplications
2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3-5, 2024, Proceedings,
Part I, edited by Stephen L. Smith et al., vol. 14634, Springer, 2024, pp.
305–321, doi:10.1007/978-3-031-56852-7_20.
short: 'O.L. Preuß, J. Rook, H. Trautmann, in: S.L. Smith, J. Correia, C. Cintrano
(Eds.), Applications of Evolutionary Computation - 27th European Conference, EvoApplications
2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3-5, 2024, Proceedings,
Part I, Springer, 2024, pp. 305–321.'
date_created: 2025-06-04T12:47:35Z
date_updated: 2025-06-05T06:01:02Z
doi: 10.1007/978-3-031-56852-7_20
editor:
- first_name: Stephen L.
full_name: Smith, Stephen L.
last_name: Smith
- first_name: João
full_name: Correia, João
last_name: Correia
- first_name: Christian
full_name: Cintrano, Christian
last_name: Cintrano
intvolume: ' 14634'
language:
- iso: eng
page: 305–321
publication: Applications of Evolutionary Computation - 27th European Conference,
EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3-5,
2024, Proceedings, Part I
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal
Multi-objective Optimisation Problems
type: conference
user_id: '15504'
volume: 14634
year: '2024'
...
---
_id: '60132'
author:
- first_name: Moritz
full_name: Seiler, Moritz
id: '105520'
last_name: Seiler
- first_name: Urban
full_name: Skvorc, Urban
id: '103764'
last_name: Skvorc
- first_name: Gjorgjina
full_name: Cenikj, Gjorgjina
last_name: Cenikj
- first_name: Carola
full_name: Doerr, Carola
last_name: Doerr
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Seiler M, Skvorc U, Cenikj G, Doerr C, Trautmann H. Learned Features vs. Classical
ELA on Affine BBOB Functions. In: Affenzeller M, Winkler SM, Kononova AV, et al.,
eds. Parallel Problem Solving from Nature - PPSN XVIII - 18th International
Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings,
Part II. Vol 15149. Lecture Notes in Computer Science. Springer; 2024:137–153.
doi:10.1007/978-3-031-70068-2_9'
apa: Seiler, M., Skvorc, U., Cenikj, G., Doerr, C., & Trautmann, H. (2024).
Learned Features vs. Classical ELA on Affine BBOB Functions. In M. Affenzeller,
S. M. Winkler, A. V. Kononova, H. Trautmann, T. Tusar, P. Machado, & T. Bäck
(Eds.), Parallel Problem Solving from Nature - PPSN XVIII - 18th International
Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings,
Part II (Vol. 15149, pp. 137–153). Springer. https://doi.org/10.1007/978-3-031-70068-2_9
bibtex: '@inproceedings{Seiler_Skvorc_Cenikj_Doerr_Trautmann_2024, series={Lecture
Notes in Computer Science}, title={Learned Features vs. Classical ELA on Affine
BBOB Functions}, volume={15149}, DOI={10.1007/978-3-031-70068-2_9},
booktitle={Parallel Problem Solving from Nature - PPSN XVIII - 18th International
Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings,
Part II}, publisher={Springer}, author={Seiler, Moritz and Skvorc, Urban and Cenikj,
Gjorgjina and Doerr, Carola and Trautmann, Heike}, editor={Affenzeller, Michael
and Winkler, Stephan M. and Kononova, Anna V. and Trautmann, Heike and Tusar,
Tea and Machado, Penousal and Bäck, Thomas}, year={2024}, pages={137–153}, collection={Lecture
Notes in Computer Science} }'
chicago: Seiler, Moritz, Urban Skvorc, Gjorgjina Cenikj, Carola Doerr, and Heike
Trautmann. “Learned Features vs. Classical ELA on Affine BBOB Functions.” In Parallel
Problem Solving from Nature - PPSN XVIII - 18th International Conference, PPSN
2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part II, edited
by Michael Affenzeller, Stephan M. Winkler, Anna V. Kononova, Heike Trautmann,
Tea Tusar, Penousal Machado, and Thomas Bäck, 15149:137–153. Lecture Notes in
Computer Science. Springer, 2024. https://doi.org/10.1007/978-3-031-70068-2_9.
ieee: 'M. Seiler, U. Skvorc, G. Cenikj, C. Doerr, and H. Trautmann, “Learned Features
vs. Classical ELA on Affine BBOB Functions,” in Parallel Problem Solving from
Nature - PPSN XVIII - 18th International Conference, PPSN 2024, Hagenberg, Austria,
September 14-18, 2024, Proceedings, Part II, 2024, vol. 15149, pp. 137–153,
doi: 10.1007/978-3-031-70068-2_9.'
mla: Seiler, Moritz, et al. “Learned Features vs. Classical ELA on Affine BBOB Functions.”
Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference,
PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part II,
edited by Michael Affenzeller et al., vol. 15149, Springer, 2024, pp. 137–153,
doi:10.1007/978-3-031-70068-2_9.
short: 'M. Seiler, U. Skvorc, G. Cenikj, C. Doerr, H. Trautmann, in: M. Affenzeller,
S.M. Winkler, A.V. Kononova, H. Trautmann, T. Tusar, P. Machado, T. Bäck (Eds.),
Parallel Problem Solving from Nature - PPSN XVIII - 18th International Conference,
PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part II, Springer,
2024, pp. 137–153.'
date_created: 2025-06-04T12:48:56Z
date_updated: 2025-06-04T12:49:30Z
doi: 10.1007/978-3-031-70068-2_9
editor:
- first_name: Michael
full_name: Affenzeller, Michael
last_name: Affenzeller
- first_name: Stephan M.
full_name: Winkler, Stephan M.
last_name: Winkler
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
- first_name: Tea
full_name: Tusar, Tea
last_name: Tusar
- first_name: Penousal
full_name: Machado, Penousal
last_name: Machado
- first_name: Thomas
full_name: Bäck, Thomas
last_name: Bäck
intvolume: ' 15149'
language:
- iso: eng
page: 137–153
publication: Parallel Problem Solving from Nature - PPSN XVIII - 18th International
Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part
II
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Learned Features vs. Classical ELA on Affine BBOB Functions
type: conference
user_id: '15504'
volume: 15149
year: '2024'
...
---
_id: '59283'
author:
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Prager RP, Trautmann H. Pflacco: Feature-Based Landscape Analysis of Continuous
and Constrained Optimization Problems in Python. Evol Comput. 2024;32(3):211–216.
doi:10.1162/EVCO_A_00341'
apa: 'Prager, R. P., & Trautmann, H. (2024). Pflacco: Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems in Python. Evol.
Comput., 32(3), 211–216. https://doi.org/10.1162/EVCO_A_00341'
bibtex: '@article{Prager_Trautmann_2024, title={Pflacco: Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems in Python}, volume={32},
DOI={10.1162/EVCO_A_00341},
number={3}, journal={Evol. Comput.}, author={Prager, Raphael Patrick and Trautmann,
Heike}, year={2024}, pages={211–216} }'
chicago: 'Prager, Raphael Patrick, and Heike Trautmann. “Pflacco: Feature-Based
Landscape Analysis of Continuous and Constrained Optimization Problems in Python.”
Evol. Comput. 32, no. 3 (2024): 211–216. https://doi.org/10.1162/EVCO_A_00341.'
ieee: 'R. P. Prager and H. Trautmann, “Pflacco: Feature-Based Landscape Analysis
of Continuous and Constrained Optimization Problems in Python,” Evol. Comput.,
vol. 32, no. 3, pp. 211–216, 2024, doi: 10.1162/EVCO_A_00341.'
mla: 'Prager, Raphael Patrick, and Heike Trautmann. “Pflacco: Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems in Python.” Evol.
Comput., vol. 32, no. 3, 2024, pp. 211–216, doi:10.1162/EVCO_A_00341.'
short: R.P. Prager, H. Trautmann, Evol. Comput. 32 (2024) 211–216.
date_created: 2025-04-03T05:56:07Z
date_updated: 2025-04-03T05:56:33Z
doi: 10.1162/EVCO_A_00341
intvolume: ' 32'
issue: '3'
language:
- iso: eng
page: 211–216
publication: Evol. Comput.
status: public
title: 'Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization
Problems in Python'
type: journal_article
user_id: '15504'
volume: 32
year: '2024'
...
---
_id: '47522'
abstract:
- lang: eng
text: Artificial benchmark functions are commonly used in optimization research
because of their ability to rapidly evaluate potential solutions, making them
a preferred substitute for real-world problems. However, these benchmark functions
have faced criticism for their limited resemblance to real-world problems. In
response, recent research has focused on automatically generating new benchmark
functions for areas where established test suites are inadequate. These approaches
have limitations, such as the difficulty of generating new benchmark functions
that exhibit exploratory landscape analysis (ELA) features beyond those of existing
benchmarks.The objective of this work is to develop a method for generating benchmark
functions for single-objective continuous optimization with user-specified structural
properties. Specifically, we aim to demonstrate a proof of concept for a method
that uses an ELA feature vector to specify these properties in advance. To achieve
this, we begin by generating a random sample of decision space variables and objective
values. We then adjust the objective values using CMA-ES until the corresponding
features of our new problem match the predefined ELA features within a specified
threshold. By iteratively transforming the landscape in this way, we ensure that
the resulting function exhibits the desired properties. To create the final function,
we use the resulting point cloud as training data for a simple neural network
that produces a function exhibiting the target ELA features. We demonstrate the
effectiveness of this approach by replicating the existing functions of the well-known
BBOB suite and creating new functions with ELA feature values that are not present
in BBOB.
author:
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Konstantin
full_name: Dietrich, Konstantin
last_name: Dietrich
- first_name: Lennart
full_name: Schneider, Lennart
last_name: Schneider
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Bernd
full_name: Bischl, Bernd
last_name: Bischl
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Olaf
full_name: Mersmann, Olaf
last_name: Mersmann
citation:
ama: 'Prager RP, Dietrich K, Schneider L, et al. Neural Networks as Black-Box Benchmark
Functions Optimized for Exploratory Landscape Features. In: Proceedings of
the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. FOGA
’23. Association for Computing Machinery; 2023:129–139. doi:10.1145/3594805.3607136'
apa: Prager, R. P., Dietrich, K., Schneider, L., Schäpermeier, L., Bischl, B., Kerschke,
P., Trautmann, H., & Mersmann, O. (2023). Neural Networks as Black-Box Benchmark
Functions Optimized for Exploratory Landscape Features. Proceedings of the
17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 129–139.
https://doi.org/10.1145/3594805.3607136
bibtex: '@inproceedings{Prager_Dietrich_Schneider_Schäpermeier_Bischl_Kerschke_Trautmann_Mersmann_2023,
place={New York, NY, USA}, series={FOGA ’23}, title={Neural Networks as Black-Box
Benchmark Functions Optimized for Exploratory Landscape Features}, DOI={10.1145/3594805.3607136},
booktitle={Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic
Algorithms}, publisher={Association for Computing Machinery}, author={Prager,
Raphael Patrick and Dietrich, Konstantin and Schneider, Lennart and Schäpermeier,
Lennart and Bischl, Bernd and Kerschke, Pascal and Trautmann, Heike and Mersmann,
Olaf}, year={2023}, pages={129–139}, collection={FOGA ’23} }'
chicago: 'Prager, Raphael Patrick, Konstantin Dietrich, Lennart Schneider, Lennart
Schäpermeier, Bernd Bischl, Pascal Kerschke, Heike Trautmann, and Olaf Mersmann.
“Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape
Features.” In Proceedings of the 17th ACM/SIGEVO Conference on Foundations
of Genetic Algorithms, 129–139. FOGA ’23. New York, NY, USA: Association for
Computing Machinery, 2023. https://doi.org/10.1145/3594805.3607136.'
ieee: 'R. P. Prager et al., “Neural Networks as Black-Box Benchmark Functions
Optimized for Exploratory Landscape Features,” in Proceedings of the 17th ACM/SIGEVO
Conference on Foundations of Genetic Algorithms, 2023, pp. 129–139, doi: 10.1145/3594805.3607136.'
mla: Prager, Raphael Patrick, et al. “Neural Networks as Black-Box Benchmark Functions
Optimized for Exploratory Landscape Features.” Proceedings of the 17th ACM/SIGEVO
Conference on Foundations of Genetic Algorithms, Association for Computing
Machinery, 2023, pp. 129–139, doi:10.1145/3594805.3607136.
short: 'R.P. Prager, K. Dietrich, L. Schneider, L. Schäpermeier, B. Bischl, P. Kerschke,
H. Trautmann, O. Mersmann, in: Proceedings of the 17th ACM/SIGEVO Conference on
Foundations of Genetic Algorithms, Association for Computing Machinery, New York,
NY, USA, 2023, pp. 129–139.'
date_created: 2023-09-27T15:43:17Z
date_updated: 2023-10-16T12:33:02Z
department:
- _id: '34'
- _id: '819'
doi: 10.1145/3594805.3607136
keyword:
- Benchmarking
- Instance Generator
- Black-Box Continuous Optimization
- Exploratory Landscape Analysis
- Neural Networks
language:
- iso: eng
page: 129–139
place: New York, NY, USA
publication: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic
Algorithms
publication_identifier:
isbn:
- '9798400702020'
publisher: Association for Computing Machinery
series_title: FOGA ’23
status: public
title: Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory
Landscape Features
type: conference
user_id: '15504'
year: '2023'
...
---
_id: '46297'
abstract:
- lang: eng
text: Exploratory landscape analysis (ELA) in single-objective black-box optimization
relies on a comprehensive and large set of numerical features characterizing problem
instances. Those foster problem understanding and serve as basis for constructing
automated algorithm selection models choosing the best suited algorithm for a
problem at hand based on the aforementioned features computed prior to optimization.
This work specifically points to the sensitivity of a substantial proportion of
these features to absolute objective values, i.e., we observe a lack of shift
and scale invariance. We show that this unfortunately induces bias within automated
algorithm selection models, an overfitting to specific benchmark problem sets
used for training and thereby hinders generalization capabilities to unseen problems.
We tackle these issues by presenting an appropriate objective normalization to
be used prior to ELA feature computation and empirically illustrate the respective
effectiveness focusing on the BBOB benchmark set.
author:
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Prager RP, Trautmann H. Nullifying the Inherent Bias of Non-invariant Exploratory
Landscape Analysis Features. In: Correia J, Smith S, Qaddoura R, eds. Applications
of Evolutionary Computation. Springer Nature Switzerland; 2023:411–425.'
apa: Prager, R. P., & Trautmann, H. (2023). Nullifying the Inherent Bias of
Non-invariant Exploratory Landscape Analysis Features. In J. Correia, S. Smith,
& R. Qaddoura (Eds.), Applications of Evolutionary Computation (pp.
411–425). Springer Nature Switzerland.
bibtex: '@inproceedings{Prager_Trautmann_2023, place={Cham}, title={Nullifying the
Inherent Bias of Non-invariant Exploratory Landscape Analysis Features}, booktitle={Applications
of Evolutionary Computation}, publisher={Springer Nature Switzerland}, author={Prager,
Raphael Patrick and Trautmann, Heike}, editor={Correia, João and Smith, Stephen
and Qaddoura, Raneem}, year={2023}, pages={411–425} }'
chicago: 'Prager, Raphael Patrick, and Heike Trautmann. “Nullifying the Inherent
Bias of Non-Invariant Exploratory Landscape Analysis Features.” In Applications
of Evolutionary Computation, edited by João Correia, Stephen Smith, and Raneem
Qaddoura, 411–425. Cham: Springer Nature Switzerland, 2023.'
ieee: R. P. Prager and H. Trautmann, “Nullifying the Inherent Bias of Non-invariant
Exploratory Landscape Analysis Features,” in Applications of Evolutionary Computation,
2023, pp. 411–425.
mla: Prager, Raphael Patrick, and Heike Trautmann. “Nullifying the Inherent Bias
of Non-Invariant Exploratory Landscape Analysis Features.” Applications of
Evolutionary Computation, edited by João Correia et al., Springer Nature Switzerland,
2023, pp. 411–425.
short: 'R.P. Prager, H. Trautmann, in: J. Correia, S. Smith, R. Qaddoura (Eds.),
Applications of Evolutionary Computation, Springer Nature Switzerland, Cham, 2023,
pp. 411–425.'
date_created: 2023-08-04T06:54:22Z
date_updated: 2023-10-16T12:36:45Z
department:
- _id: '819'
- _id: '34'
editor:
- first_name: João
full_name: Correia, João
last_name: Correia
- first_name: Stephen
full_name: Smith, Stephen
last_name: Smith
- first_name: Raneem
full_name: Qaddoura, Raneem
last_name: Qaddoura
language:
- iso: eng
page: 411–425
place: Cham
publication: Applications of Evolutionary Computation
publication_identifier:
isbn:
- 978-3-031-30229-9
publisher: Springer Nature Switzerland
status: public
title: Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis
Features
type: conference
user_id: '15504'
year: '2023'
...
---
_id: '46298'
abstract:
- lang: eng
text: The design and choice of benchmark suites are ongoing topics of discussion
in the multi-objective optimization community. Some suites provide a good understanding
of their Pareto sets and fronts, such as the well-known DTLZ and ZDT problems.
However, they lack diversity in their landscape properties and do not provide
a mechanism for creating multiple distinct problem instances. Other suites, like
bi-objective BBOB, possess diverse and challenging landscape properties, but their
optima are not well understood and can only be approximated empirically without
any guarantees.
author:
- first_name: Lennart
full_name: Schäpermeier, Lennart
last_name: Schäpermeier
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Schäpermeier L, Kerschke P, Grimme C, Trautmann H. Peak-A-Boo! Generating
Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets. In:
Emmerich M, Deutz A, Wang H, et al., eds. Evolutionary Multi-Criterion Optimization.
Springer Nature Switzerland; 2023:291–304.'
apa: Schäpermeier, L., Kerschke, P., Grimme, C., & Trautmann, H. (2023). Peak-A-Boo!
Generating Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto
Sets. In M. Emmerich, A. Deutz, H. Wang, A. V. Kononova, B. Naujoks, K. Li, K.
Miettinen, & I. Yevseyeva (Eds.), Evolutionary Multi-Criterion Optimization
(pp. 291–304). Springer Nature Switzerland.
bibtex: '@inproceedings{Schäpermeier_Kerschke_Grimme_Trautmann_2023, place={Cham},
title={Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems
with Precise Pareto Sets}, booktitle={Evolutionary Multi-Criterion Optimization},
publisher={Springer Nature Switzerland}, author={Schäpermeier, Lennart and Kerschke,
Pascal and Grimme, Christian and Trautmann, Heike}, editor={Emmerich, Michael
and Deutz, André and Wang, Hao and Kononova, Anna V. and Naujoks, Boris and Li,
Ke and Miettinen, Kaisa and Yevseyeva, Iryna}, year={2023}, pages={291–304} }'
chicago: 'Schäpermeier, Lennart, Pascal Kerschke, Christian Grimme, and Heike Trautmann.
“Peak-A-Boo! Generating Multi-Objective Multiple Peaks Benchmark Problems with
Precise Pareto Sets.” In Evolutionary Multi-Criterion Optimization, edited
by Michael Emmerich, André Deutz, Hao Wang, Anna V. Kononova, Boris Naujoks, Ke
Li, Kaisa Miettinen, and Iryna Yevseyeva, 291–304. Cham: Springer Nature Switzerland,
2023.'
ieee: L. Schäpermeier, P. Kerschke, C. Grimme, and H. Trautmann, “Peak-A-Boo! Generating
Multi-objective Multiple Peaks Benchmark Problems with Precise Pareto Sets,” in
Evolutionary Multi-Criterion Optimization, 2023, pp. 291–304.
mla: Schäpermeier, Lennart, et al. “Peak-A-Boo! Generating Multi-Objective Multiple
Peaks Benchmark Problems with Precise Pareto Sets.” Evolutionary Multi-Criterion
Optimization, edited by Michael Emmerich et al., Springer Nature Switzerland,
2023, pp. 291–304.
short: 'L. Schäpermeier, P. Kerschke, C. Grimme, H. Trautmann, in: M. Emmerich,
A. Deutz, H. Wang, A.V. Kononova, B. Naujoks, K. Li, K. Miettinen, I. Yevseyeva
(Eds.), Evolutionary Multi-Criterion Optimization, Springer Nature Switzerland,
Cham, 2023, pp. 291–304.'
date_created: 2023-08-04T06:56:10Z
date_updated: 2023-10-16T12:36:17Z
department:
- _id: '819'
- _id: '34'
editor:
- first_name: Michael
full_name: Emmerich, Michael
last_name: Emmerich
- first_name: André
full_name: Deutz, André
last_name: Deutz
- first_name: Hao
full_name: Wang, Hao
last_name: Wang
- first_name: Anna V.
full_name: Kononova, Anna V.
last_name: Kononova
- first_name: Boris
full_name: Naujoks, Boris
last_name: Naujoks
- first_name: Ke
full_name: Li, Ke
last_name: Li
- first_name: Kaisa
full_name: Miettinen, Kaisa
last_name: Miettinen
- first_name: Iryna
full_name: Yevseyeva, Iryna
last_name: Yevseyeva
language:
- iso: eng
page: 291–304
place: Cham
publication: Evolutionary Multi-Criterion Optimization
publication_identifier:
isbn:
- 978-3-031-27250-9
publisher: Springer Nature Switzerland
status: public
title: Peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with
Precise Pareto Sets
type: conference
user_id: '15504'
year: '2023'
...
---
_id: '46299'
abstract:
- lang: eng
text: The herein proposed Python package pflacco provides a set of numerical features
to characterize single-objective continuous and constrained optimization problems.
Thereby, pflacco addresses two major challenges in the area optimization. Firstly,
it provides the means to develop an understanding of a given problem instance,
which is crucial for designing, selecting, or configuring optimization algorithms
in general. Secondly, these numerical features can be utilized in the research
streams of automated algorithm selection and configuration. While the majority
of these landscape features is already available in the R package flacco, our
Python implementation offers these tools to an even wider audience and thereby
promotes research interests and novel avenues in the area of optimization.
author:
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Prager RP, Trautmann H. Pflacco: Feature-Based Landscape Analysis of Continuous
and Constrained Optimization Problems in Python. Evolutionary Computation.
Published online 2023:1–25. doi:10.1162/evco_a_00341'
apa: 'Prager, R. P., & Trautmann, H. (2023). Pflacco: Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems in Python. Evolutionary
Computation, 1–25. https://doi.org/10.1162/evco_a_00341'
bibtex: '@article{Prager_Trautmann_2023, title={Pflacco: Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems in Python}, DOI={10.1162/evco_a_00341}, journal={Evolutionary
Computation}, author={Prager, Raphael Patrick and Trautmann, Heike}, year={2023},
pages={1–25} }'
chicago: 'Prager, Raphael Patrick, and Heike Trautmann. “Pflacco: Feature-Based
Landscape Analysis of Continuous and Constrained Optimization Problems in Python.”
Evolutionary Computation, 2023, 1–25. https://doi.org/10.1162/evco_a_00341.'
ieee: 'R. P. Prager and H. Trautmann, “Pflacco: Feature-Based Landscape Analysis
of Continuous and Constrained Optimization Problems in Python,” Evolutionary
Computation, pp. 1–25, 2023, doi: 10.1162/evco_a_00341.'
mla: 'Prager, Raphael Patrick, and Heike Trautmann. “Pflacco: Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems in Python.” Evolutionary
Computation, 2023, pp. 1–25, doi:10.1162/evco_a_00341.'
short: R.P. Prager, H. Trautmann, Evolutionary Computation (2023) 1–25.
date_created: 2023-08-04T07:01:33Z
date_updated: 2023-10-16T12:35:56Z
department:
- _id: '819'
- _id: '34'
doi: 10.1162/evco_a_00341
language:
- iso: eng
page: 1–25
publication: Evolutionary Computation
publication_identifier:
issn:
- 1063-6560
status: public
title: 'Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization
Problems in Python'
type: journal_article
user_id: '15504'
year: '2023'
...
---
_id: '52530'
author:
- first_name: Raphael Patrick
full_name: Prager, Raphael Patrick
last_name: Prager
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Prager RP, Trautmann H. Investigating the Viability of Existing Exploratory
Landscape Analysis Features for Mixed-Integer Problems. In: Silva S, Paquete L,
eds. Companion Proceedings of the Conference on Genetic and Evolutionary Computation,
GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023. ACM; 2023:451–454.
doi:10.1145/3583133.3590757'
apa: Prager, R. P., & Trautmann, H. (2023). Investigating the Viability of Existing
Exploratory Landscape Analysis Features for Mixed-Integer Problems. In S. Silva
& L. Paquete (Eds.), Companion Proceedings of the Conference on Genetic
and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal,
July 15-19, 2023 (pp. 451–454). ACM. https://doi.org/10.1145/3583133.3590757
bibtex: '@inproceedings{Prager_Trautmann_2023, title={Investigating the Viability
of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems},
DOI={10.1145/3583133.3590757},
booktitle={Companion Proceedings of the Conference on Genetic and Evolutionary
Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023},
publisher={ACM}, author={Prager, Raphael Patrick and Trautmann, Heike}, editor={Silva,
Sara and Paquete, Luís}, year={2023}, pages={451–454} }'
chicago: Prager, Raphael Patrick, and Heike Trautmann. “Investigating the Viability
of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems.”
In Companion Proceedings of the Conference on Genetic and Evolutionary Computation,
GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023, edited by
Sara Silva and Luís Paquete, 451–454. ACM, 2023. https://doi.org/10.1145/3583133.3590757.
ieee: 'R. P. Prager and H. Trautmann, “Investigating the Viability of Existing Exploratory
Landscape Analysis Features for Mixed-Integer Problems,” in Companion Proceedings
of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion
Volume, Lisbon, Portugal, July 15-19, 2023, 2023, pp. 451–454, doi: 10.1145/3583133.3590757.'
mla: Prager, Raphael Patrick, and Heike Trautmann. “Investigating the Viability
of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems.”
Companion Proceedings of the Conference on Genetic and Evolutionary Computation,
GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023, edited by
Sara Silva and Luís Paquete, ACM, 2023, pp. 451–454, doi:10.1145/3583133.3590757.
short: 'R.P. Prager, H. Trautmann, in: S. Silva, L. Paquete (Eds.), Companion Proceedings
of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion
Volume, Lisbon, Portugal, July 15-19, 2023, ACM, 2023, pp. 451–454.'
date_created: 2024-03-13T09:55:17Z
date_updated: 2024-03-13T10:28:07Z
department:
- _id: '819'
doi: 10.1145/3583133.3590757
editor:
- first_name: Sara
full_name: Silva, Sara
last_name: Silva
- first_name: Luís
full_name: Paquete, Luís
last_name: Paquete
language:
- iso: eng
page: 451–454
publication: Companion Proceedings of the Conference on Genetic and Evolutionary Computation,
GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023
publisher: ACM
status: public
title: Investigating the Viability of Existing Exploratory Landscape Analysis Features
for Mixed-Integer Problems
type: conference
user_id: '15504'
year: '2023'
...
---
_id: '46310'
abstract:
- lang: eng
text: 'Classic automated algorithm selection (AS) for (combinatorial) optimization
problems heavily relies on so-called instance features, i.e., numerical characteristics
of the problem at hand ideally extracted with computationally low-demanding routines.
For the traveling salesperson problem (TSP) a plethora of features have been suggested.
Most of these features are, if at all, only normalized imprecisely raising the
issue of feature values being strongly affected by the instance size. Such artifacts
may have detrimental effects on algorithm selection models. We propose a normalization
for two feature groups which stood out in multiple AS studies on the TSP: (a)
features based on a minimum spanning tree (MST) and (b) nearest neighbor relationships
of the input instance. To this end we theoretically derive minimum and maximum
values for properties of MSTs and k-nearest neighbor graphs (NNG) of Euclidean
graphs. We analyze the differences in feature space between normalized versions
of these features and their unnormalized counterparts. Our empirical investigations
on various TSP benchmark sets point out that the feature scaling succeeds in eliminating
the effect of the instance size. A proof-of-concept AS-study shows promising results:
models trained with normalized features tend to outperform those trained with
the respective vanilla features.'
author:
- first_name: Jonathan
full_name: Heins, Jonathan
last_name: Heins
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Janina
full_name: Pohl, Janina
last_name: Pohl
- first_name: Moritz
full_name: Seiler, Moritz
id: '105520'
last_name: Seiler
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
citation:
ama: Heins J, Bossek J, Pohl J, Seiler M, Trautmann H, Kerschke P. A study on the
effects of normalized TSP features for automated algorithm selection. Theoretical
Computer Science. 2023;940:123-145. doi:https://doi.org/10.1016/j.tcs.2022.10.019
apa: Heins, J., Bossek, J., Pohl, J., Seiler, M., Trautmann, H., & Kerschke,
P. (2023). A study on the effects of normalized TSP features for automated algorithm
selection. Theoretical Computer Science, 940, 123–145. https://doi.org/10.1016/j.tcs.2022.10.019
bibtex: '@article{Heins_Bossek_Pohl_Seiler_Trautmann_Kerschke_2023, title={A study
on the effects of normalized TSP features for automated algorithm selection},
volume={940}, DOI={https://doi.org/10.1016/j.tcs.2022.10.019},
journal={Theoretical Computer Science}, author={Heins, Jonathan and Bossek, Jakob
and Pohl, Janina and Seiler, Moritz and Trautmann, Heike and Kerschke, Pascal},
year={2023}, pages={123–145} }'
chicago: 'Heins, Jonathan, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann,
and Pascal Kerschke. “A Study on the Effects of Normalized TSP Features for Automated
Algorithm Selection.” Theoretical Computer Science 940 (2023): 123–45.
https://doi.org/10.1016/j.tcs.2022.10.019.'
ieee: 'J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, and P. Kerschke, “A
study on the effects of normalized TSP features for automated algorithm selection,”
Theoretical Computer Science, vol. 940, pp. 123–145, 2023, doi: https://doi.org/10.1016/j.tcs.2022.10.019.'
mla: Heins, Jonathan, et al. “A Study on the Effects of Normalized TSP Features
for Automated Algorithm Selection.” Theoretical Computer Science, vol.
940, 2023, pp. 123–45, doi:https://doi.org/10.1016/j.tcs.2022.10.019.
short: J. Heins, J. Bossek, J. Pohl, M. Seiler, H. Trautmann, P. Kerschke, Theoretical
Computer Science 940 (2023) 123–145.
date_created: 2023-08-04T07:18:38Z
date_updated: 2024-06-10T11:57:21Z
department:
- _id: '34'
- _id: '819'
doi: https://doi.org/10.1016/j.tcs.2022.10.019
intvolume: ' 940'
keyword:
- Feature normalization
- Algorithm selection
- Traveling salesperson problem
language:
- iso: eng
page: 123-145
publication: Theoretical Computer Science
publication_identifier:
issn:
- 0304-3975
status: public
title: A study on the effects of normalized TSP features for automated algorithm selection
type: journal_article
user_id: '15504'
volume: 940
year: '2023'
...
---
_id: '48898'
abstract:
- lang: eng
text: 'Automated Algorithm Configuration (AAC) usually takes a global perspective:
it identifies a parameter configuration for an (optimization) algorithm that maximizes
a performance metric over a set of instances. However, the optimal choice of parameters
strongly depends on the instance at hand and should thus be calculated on a per-instance
basis. We explore the potential of Per-Instance Algorithm Configuration (PIAC)
by using Reinforcement Learning (RL). To this end, we propose a novel PIAC approach
that is based on deep neural networks. We apply it to predict configurations for
the Lin\textendash Kernighan heuristic (LKH) for the Traveling Salesperson Problem
(TSP) individually for every single instance. To train our PIAC approach, we create
a large set of 100000 TSP instances with 2000 nodes each \textemdash currently
the largest benchmark set to the best of our knowledge. We compare our approach
to the state-of-the-art AAC method Sequential Model-based Algorithm Configuration
(SMAC). The results show that our PIAC approach outperforms this baseline on both
the newly created instance set and established instance sets.'
author:
- first_name: Moritz
full_name: Seiler, Moritz
id: '105520'
last_name: Seiler
- first_name: Jeroen
full_name: Rook, Jeroen
last_name: Rook
- first_name: Jonathan
full_name: Heins, Jonathan
last_name: Heins
- first_name: Oliver Ludger
full_name: Preuß, Oliver Ludger
id: '102978'
last_name: Preuß
orcid: 0009-0008-9308-2418
- first_name: Jakob
full_name: Bossek, Jakob
id: '102979'
last_name: Bossek
orcid: 0000-0002-4121-4668
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Seiler M, Rook J, Heins J, Preuß OL, Bossek J, Trautmann H. Using Reinforcement
Learning for Per-Instance Algorithm Configuration on the TSP. In: 2023 IEEE
Symposium Series on Computational Intelligence (SSCI). ; :361-368. doi:10.1109/SSCI52147.2023.10372008'
apa: Seiler, M., Rook, J., Heins, J., Preuß, O. L., Bossek, J., & Trautmann,
H. (n.d.). Using Reinforcement Learning for Per-Instance Algorithm Configuration
on the TSP. 2023 IEEE Symposium Series on Computational Intelligence (SSCI),
361–368. https://doi.org/10.1109/SSCI52147.2023.10372008
bibtex: '@inproceedings{Seiler_Rook_Heins_Preuß_Bossek_Trautmann, title={Using Reinforcement
Learning for Per-Instance Algorithm Configuration on the TSP}, DOI={10.1109/SSCI52147.2023.10372008},
booktitle={2023 IEEE Symposium Series on Computational Intelligence (SSCI)}, author={Seiler,
Moritz and Rook, Jeroen and Heins, Jonathan and Preuß, Oliver Ludger and Bossek,
Jakob and Trautmann, Heike}, pages={361–368} }'
chicago: Seiler, Moritz, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob
Bossek, and Heike Trautmann. “Using Reinforcement Learning for Per-Instance Algorithm
Configuration on the TSP.” In 2023 IEEE Symposium Series on Computational Intelligence
(SSCI), 361–68, n.d. https://doi.org/10.1109/SSCI52147.2023.10372008.
ieee: 'M. Seiler, J. Rook, J. Heins, O. L. Preuß, J. Bossek, and H. Trautmann, “Using
Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP,” in
2023 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 361–368,
doi: 10.1109/SSCI52147.2023.10372008.'
mla: Seiler, Moritz, et al. “Using Reinforcement Learning for Per-Instance Algorithm
Configuration on the TSP.” 2023 IEEE Symposium Series on Computational Intelligence
(SSCI), pp. 361–68, doi:10.1109/SSCI52147.2023.10372008.
short: 'M. Seiler, J. Rook, J. Heins, O.L. Preuß, J. Bossek, H. Trautmann, in: 2023
IEEE Symposium Series on Computational Intelligence (SSCI), n.d., pp. 361–368.'
date_created: 2023-11-14T15:59:01Z
date_updated: 2024-06-10T11:56:58Z
department:
- _id: '819'
doi: 10.1109/SSCI52147.2023.10372008
extern: '1'
language:
- iso: eng
page: 361 - 368
publication: 2023 IEEE Symposium Series on Computational Intelligence (SSCI)
publication_status: accepted
status: public
title: Using Reinforcement Learning for Per-Instance Algorithm Configuration on the
TSP
type: conference
user_id: '15504'
year: '2023'
...
---
_id: '46300'
author:
- first_name: Marco
full_name: Niemann, Marco
last_name: Niemann
- first_name: Dennis
full_name: Assenmacher, Dennis
last_name: Assenmacher
- first_name: Jens
full_name: Brunk, Jens
last_name: Brunk
- first_name: Dennis Maximilian
full_name: Riehle, Dennis Maximilian
last_name: Riehle
- first_name: Jörg
full_name: Becker, Jörg
last_name: Becker
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Niemann M, Assenmacher D, Brunk J, Riehle DM, Becker J, Trautmann H. (Semi-)Automatische
Kommentarmoderation zur Erhaltung Konstruktiver Diskurse. In: Weitzel G, Mündges
S, eds. Hate Speech — Definitionen, Ausprägungen, Lösungen. VS Verlag für
Sozialwissenschaften; 2022:249–274. doi:10.1007/978-3-658-35658-3_13'
apa: Niemann, M., Assenmacher, D., Brunk, J., Riehle, D. M., Becker, J., & Trautmann,
H. (2022). (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver
Diskurse. In G. Weitzel & S. Mündges (Eds.), Hate Speech — Definitionen,
Ausprägungen, Lösungen (pp. 249–274). VS Verlag für Sozialwissenschaften.
https://doi.org/10.1007/978-3-658-35658-3_13
bibtex: '@inbook{Niemann_Assenmacher_Brunk_Riehle_Becker_Trautmann_2022, place={Wiesbaden},
title={(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse},
DOI={10.1007/978-3-658-35658-3_13},
booktitle={Hate Speech — Definitionen, Ausprägungen, Lösungen}, publisher={VS
Verlag für Sozialwissenschaften}, author={Niemann, Marco and Assenmacher, Dennis
and Brunk, Jens and Riehle, Dennis Maximilian and Becker, Jörg and Trautmann,
Heike}, editor={Weitzel, Gerrit and Mündges, Stephan}, year={2022}, pages={249–274}
}'
chicago: 'Niemann, Marco, Dennis Assenmacher, Jens Brunk, Dennis Maximilian Riehle,
Jörg Becker, and Heike Trautmann. “(Semi-)Automatische Kommentarmoderation Zur
Erhaltung Konstruktiver Diskurse.” In Hate Speech — Definitionen, Ausprägungen,
Lösungen, edited by Gerrit Weitzel and Stephan Mündges, 249–274. Wiesbaden:
VS Verlag für Sozialwissenschaften, 2022. https://doi.org/10.1007/978-3-658-35658-3_13.'
ieee: 'M. Niemann, D. Assenmacher, J. Brunk, D. M. Riehle, J. Becker, and H. Trautmann,
“(Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse,”
in Hate Speech — Definitionen, Ausprägungen, Lösungen, G. Weitzel and S.
Mündges, Eds. Wiesbaden: VS Verlag für Sozialwissenschaften, 2022, pp. 249–274.'
mla: Niemann, Marco, et al. “(Semi-)Automatische Kommentarmoderation Zur Erhaltung
Konstruktiver Diskurse.” Hate Speech — Definitionen, Ausprägungen, Lösungen,
edited by Gerrit Weitzel and Stephan Mündges, VS Verlag für Sozialwissenschaften,
2022, pp. 249–274, doi:10.1007/978-3-658-35658-3_13.
short: 'M. Niemann, D. Assenmacher, J. Brunk, D.M. Riehle, J. Becker, H. Trautmann,
in: G. Weitzel, S. Mündges (Eds.), Hate Speech — Definitionen, Ausprägungen, Lösungen,
VS Verlag für Sozialwissenschaften, Wiesbaden, 2022, pp. 249–274.'
date_created: 2023-08-04T07:03:47Z
date_updated: 2023-10-16T12:35:41Z
department:
- _id: '819'
- _id: '34'
doi: 10.1007/978-3-658-35658-3_13
editor:
- first_name: Gerrit
full_name: Weitzel, Gerrit
last_name: Weitzel
- first_name: Stephan
full_name: Mündges, Stephan
last_name: Mündges
language:
- iso: eng
page: 249–274
place: Wiesbaden
publication: Hate Speech — Definitionen, Ausprägungen, Lösungen
publication_identifier:
isbn:
- 978-3-658-35658-3
publisher: VS Verlag für Sozialwissenschaften
status: public
title: (Semi-)Automatische Kommentarmoderation zur Erhaltung Konstruktiver Diskurse
type: book_chapter
user_id: '15504'
year: '2022'
...